{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import json\n",
    "import pandas as pd\n",
    "import random\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "from math import pi, cos, sin\n",
    "import cv2 as cv\n",
    "import matplotlib.pyplot as plt\n",
    "import shutil\n",
    "from circum import xy_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(\"/home/kiprono/Documents/STELLENBOSCH UNIVERISTY/Masters by Research/\\\n",
    "Mask RCNN/Annotation projects/ACFR/apples\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_csv = os.path.join(os.getcwd(),\"train_csv\")\n",
    "train_images = os.path.join(os.getcwd(),\"train_images\")\n",
    "filesList = os.listdir(train_csv)\n",
    "file_ = random.choice(filesList)\n",
    "df = pd.read_csv(os.path.join(train_csv,file_))\n",
    "df\n",
    "image_name = file_.replace(\".csv\",\".png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#for one csv file\n",
    "for row in range(len(df)):\n",
    "    df.at[row,\"filename\"] = image_name\n",
    "    df.at[row,\"file_size\"] = Path(os.path.join(train_images,image_name)).stat().st_size\n",
    "    img = cv.imread(os.path.join(train_images,image_name))\n",
    "    df.at[row,\"file_attributes\"] = '{}'\n",
    "    df.at[row,\"region_count\"] = len(df)\n",
    "    df.at[row,'region_id'] = row\n",
    "    t = {'name':'polygon','all_points_x':None,'all_points_y':None}\n",
    "    x,y = xy_values(df.at[row,\"c-x\"],df.at[row,\"c-y\"],df.at[row,\"radius\"],img.shape[0],img.shape[1])\n",
    "    t['all_points_x']  = x\n",
    "    t['all_points_y'] = y\n",
    "    df.at[row,'region_shape_attributes'] = object()\n",
    "    df.at[row,'region_shape_attributes'] = t\n",
    "    df.at[row,\"region_attributes\"] = '{}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#item</th>\n",
       "      <th>c-x</th>\n",
       "      <th>c-y</th>\n",
       "      <th>radius</th>\n",
       "      <th>label</th>\n",
       "      <th>filename</th>\n",
       "      <th>file_size</th>\n",
       "      <th>file_attributes</th>\n",
       "      <th>region_count</th>\n",
       "      <th>region_id</th>\n",
       "      <th>region_shape_attributes</th>\n",
       "      <th>region_attributes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>230.28</td>\n",
       "      <td>178.89</td>\n",
       "      <td>20.09</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>215.28</td>\n",
       "      <td>117.50</td>\n",
       "      <td>20.09</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>216.67</td>\n",
       "      <td>77.22</td>\n",
       "      <td>18.98</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>268.89</td>\n",
       "      <td>100.83</td>\n",
       "      <td>18.98</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>248.33</td>\n",
       "      <td>50.00</td>\n",
       "      <td>17.31</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>301.11</td>\n",
       "      <td>52.78</td>\n",
       "      <td>18.98</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>268.61</td>\n",
       "      <td>3.06</td>\n",
       "      <td>17.31</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>242.22</td>\n",
       "      <td>16.39</td>\n",
       "      <td>22.31</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>235.28</td>\n",
       "      <td>1.94</td>\n",
       "      <td>22.31</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>201.67</td>\n",
       "      <td>23.33</td>\n",
       "      <td>22.87</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>149.72</td>\n",
       "      <td>21.94</td>\n",
       "      <td>17.31</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [167, 166,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>83.61</td>\n",
       "      <td>59.17</td>\n",
       "      <td>19.81</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [103, 103,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>108.61</td>\n",
       "      <td>68.89</td>\n",
       "      <td>18.98</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798.0</td>\n",
       "      <td>{}</td>\n",
       "      <td>13.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [127, 127,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    #item     c-x     c-y  radius  label                       filename  \\\n",
       "0       0  230.28  178.89   20.09      1  20130320T013114.145799_32.png   \n",
       "1       1  215.28  117.50   20.09      1  20130320T013114.145799_32.png   \n",
       "2       2  216.67   77.22   18.98      1  20130320T013114.145799_32.png   \n",
       "3       3  268.89  100.83   18.98      1  20130320T013114.145799_32.png   \n",
       "4       4  248.33   50.00   17.31      1  20130320T013114.145799_32.png   \n",
       "5       5  301.11   52.78   18.98      1  20130320T013114.145799_32.png   \n",
       "6       6  268.61    3.06   17.31      1  20130320T013114.145799_32.png   \n",
       "7       7  242.22   16.39   22.31      1  20130320T013114.145799_32.png   \n",
       "8       8  235.28    1.94   22.31      1  20130320T013114.145799_32.png   \n",
       "9       9  201.67   23.33   22.87      1  20130320T013114.145799_32.png   \n",
       "10     10  149.72   21.94   17.31      1  20130320T013114.145799_32.png   \n",
       "11     11   83.61   59.17   19.81      1  20130320T013114.145799_32.png   \n",
       "12     12  108.61   68.89   18.98      1  20130320T013114.145799_32.png   \n",
       "\n",
       "    file_size file_attributes  region_count  region_id  \\\n",
       "0    115798.0              {}          13.0        0.0   \n",
       "1    115798.0              {}          13.0        1.0   \n",
       "2    115798.0              {}          13.0        2.0   \n",
       "3    115798.0              {}          13.0        3.0   \n",
       "4    115798.0              {}          13.0        4.0   \n",
       "5    115798.0              {}          13.0        5.0   \n",
       "6    115798.0              {}          13.0        6.0   \n",
       "7    115798.0              {}          13.0        7.0   \n",
       "8    115798.0              {}          13.0        8.0   \n",
       "9    115798.0              {}          13.0        9.0   \n",
       "10   115798.0              {}          13.0       10.0   \n",
       "11   115798.0              {}          13.0       11.0   \n",
       "12   115798.0              {}          13.0       12.0   \n",
       "\n",
       "                              region_shape_attributes region_attributes  \n",
       "0   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "1   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "2   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "3   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "4   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "5   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "6   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "7   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "8   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "9   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "10  {'name': 'polygon', 'all_points_x': [167, 166,...                {}  \n",
       "11  {'name': 'polygon', 'all_points_x': [103, 103,...                {}  \n",
       "12  {'name': 'polygon', 'all_points_x': [127, 127,...                {}  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"file_size\"] = df[\"file_size\"].astype(\"int64\")\n",
    "df[\"region_count\"] = df[\"region_count\"].astype(\"int64\")\n",
    "df['region_id'] = df['region_id'].astype(\"int64\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#item</th>\n",
       "      <th>c-x</th>\n",
       "      <th>c-y</th>\n",
       "      <th>radius</th>\n",
       "      <th>label</th>\n",
       "      <th>filename</th>\n",
       "      <th>file_size</th>\n",
       "      <th>file_attributes</th>\n",
       "      <th>region_count</th>\n",
       "      <th>region_id</th>\n",
       "      <th>region_shape_attributes</th>\n",
       "      <th>region_attributes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>230.28</td>\n",
       "      <td>178.89</td>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>215.28</td>\n",
       "      <td>117.50</td>\n",
       "      <td>20.09</td>\n",
       "      <td>1</td>\n",
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       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>216.67</td>\n",
       "      <td>77.22</td>\n",
       "      <td>18.98</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798</td>\n",
       "      <td>{}</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>268.89</td>\n",
       "      <td>100.83</td>\n",
       "      <td>18.98</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798</td>\n",
       "      <td>{}</td>\n",
       "      <td>13</td>\n",
       "      <td>3</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>248.33</td>\n",
       "      <td>50.00</td>\n",
       "      <td>17.31</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T013114.145799_32.png</td>\n",
       "      <td>115798</td>\n",
       "      <td>{}</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   #item     c-x     c-y  radius  label                       filename  \\\n",
       "0      0  230.28  178.89   20.09      1  20130320T013114.145799_32.png   \n",
       "1      1  215.28  117.50   20.09      1  20130320T013114.145799_32.png   \n",
       "2      2  216.67   77.22   18.98      1  20130320T013114.145799_32.png   \n",
       "3      3  268.89  100.83   18.98      1  20130320T013114.145799_32.png   \n",
       "4      4  248.33   50.00   17.31      1  20130320T013114.145799_32.png   \n",
       "\n",
       "   file_size file_attributes  region_count  region_id  \\\n",
       "0     115798              {}            13          0   \n",
       "1     115798              {}            13          1   \n",
       "2     115798              {}            13          2   \n",
       "3     115798              {}            13          3   \n",
       "4     115798              {}            13          4   \n",
       "\n",
       "                             region_shape_attributes region_attributes  \n",
       "0  {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "1  {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "2  {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "3  {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "4  {'name': 'polygon', 'all_points_x': [201, 201,...                {}  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LOOP ALL THROUGH IMAGES - TRAIN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kiprono/.local/lib/python3.7/site-packages/ipykernel_launcher.py:26: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
      "of pandas will change to not sort by default.\n",
      "\n",
      "To accept the future behavior, pass 'sort=False'.\n",
      "\n",
      "To retain the current behavior and silence the warning, pass 'sort=True'.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "metadf = pd.DataFrame(columns=['#item', 'c-x', 'c-y', 'radius', 'label', 'filename', 'file_size',\n",
    "       'file_attributes', 'region_count', 'region_id',\n",
    "       'region_shape_attributes', 'region_attributes'])\n",
    "\n",
    "apples = os.path.join(os.getcwd(),\"train_csv\")\n",
    "apples_images = os.path.join(os.getcwd(),\"train_images\")\n",
    "filesList = os.listdir(apples)\n",
    "for index,files in enumerate(filesList):\n",
    "    file_path = os.path.join(apples,files)\n",
    "    df = pd.read_csv(file_path)\n",
    "    image_name = files.replace(\".csv\",\".png\")\n",
    "    for row in range(len(df)):\n",
    "        df.at[row,\"filename\"] = image_name\n",
    "        img = cv.imread(os.path.join(apples_images,image_name))\n",
    "        df.at[row,\"file_size\"] = Path(os.path.join(apples_images,image_name)).stat().st_size\n",
    "        df.at[row,\"file_attributes\"] = '{}'\n",
    "        df.at[row,\"region_count\"] = len(df)\n",
    "        df.at[row,'region_id'] = row\n",
    "        t = {\"name\":\"polygon\",\"all_points_x\":None,\"all_points_y\":None}\n",
    "        x,y = xy_values(df.at[row,\"c-x\"],df.at[row,\"c-y\"],df.at[row,\"radius\"],img.shape[0],img.shape[1])\n",
    "        t['all_points_x']  = x\n",
    "        t['all_points_y'] = y\n",
    "        df.at[row,'region_shape_attributes'] = object()\n",
    "        df.at[row,'region_shape_attributes'] = t\n",
    "        df.at[row,\"region_attributes\"] = '{}'\n",
    "    metadf = pd.concat([metadf, df], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#item</th>\n",
       "      <th>c-x</th>\n",
       "      <th>c-y</th>\n",
       "      <th>file_attributes</th>\n",
       "      <th>file_size</th>\n",
       "      <th>filename</th>\n",
       "      <th>label</th>\n",
       "      <th>radius</th>\n",
       "      <th>region_attributes</th>\n",
       "      <th>region_count</th>\n",
       "      <th>region_id</th>\n",
       "      <th>region_shape_attributes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>170.62</td>\n",
       "      <td>159.69</td>\n",
       "      <td>{}</td>\n",
       "      <td>98334.0</td>\n",
       "      <td>20130320T004403.421053.Cam6_32.png</td>\n",
       "      <td>1</td>\n",
       "      <td>24.39</td>\n",
       "      <td>{}</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [195, 194,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>195.81</td>\n",
       "      <td>110.00</td>\n",
       "      <td>{}</td>\n",
       "      <td>108751.0</td>\n",
       "      <td>20130320T005044.762746.Cam6_62.png</td>\n",
       "      <td>1</td>\n",
       "      <td>13.87</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>216.13</td>\n",
       "      <td>124.19</td>\n",
       "      <td>{}</td>\n",
       "      <td>108751.0</td>\n",
       "      <td>20130320T005044.762746.Cam6_62.png</td>\n",
       "      <td>1</td>\n",
       "      <td>15.16</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>295.81</td>\n",
       "      <td>89.35</td>\n",
       "      <td>{}</td>\n",
       "      <td>108751.0</td>\n",
       "      <td>20130320T005044.762746.Cam6_62.png</td>\n",
       "      <td>1</td>\n",
       "      <td>11.29</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>87.50</td>\n",
       "      <td>62.22</td>\n",
       "      <td>{}</td>\n",
       "      <td>120851.0</td>\n",
       "      <td>20130320T005748.390478.Cam6_53.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.09</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [107, 107,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>101.67</td>\n",
       "      <td>7.22</td>\n",
       "      <td>{}</td>\n",
       "      <td>120851.0</td>\n",
       "      <td>20130320T005748.390478.Cam6_53.png</td>\n",
       "      <td>1</td>\n",
       "      <td>16.48</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [118, 118,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2</td>\n",
       "      <td>3.33</td>\n",
       "      <td>168.89</td>\n",
       "      <td>{}</td>\n",
       "      <td>120851.0</td>\n",
       "      <td>20130320T005748.390478.Cam6_53.png</td>\n",
       "      <td>1</td>\n",
       "      <td>16.48</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [19, 19, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3</td>\n",
       "      <td>35.28</td>\n",
       "      <td>165.83</td>\n",
       "      <td>{}</td>\n",
       "      <td>120851.0</td>\n",
       "      <td>20130320T005748.390478.Cam6_53.png</td>\n",
       "      <td>1</td>\n",
       "      <td>16.48</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [51, 51, 5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>151.94</td>\n",
       "      <td>13.87</td>\n",
       "      <td>{}</td>\n",
       "      <td>103340.0</td>\n",
       "      <td>20130320T004928.380174.Cam6_52.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.64</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [172, 172,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1</td>\n",
       "      <td>140.00</td>\n",
       "      <td>30.97</td>\n",
       "      <td>{}</td>\n",
       "      <td>103340.0</td>\n",
       "      <td>20130320T004928.380174.Cam6_52.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.64</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [160, 160,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2</td>\n",
       "      <td>197.10</td>\n",
       "      <td>147.10</td>\n",
       "      <td>{}</td>\n",
       "      <td>103340.0</td>\n",
       "      <td>20130320T004928.380174.Cam6_52.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.74</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>261.11</td>\n",
       "      <td>105.83</td>\n",
       "      <td>{}</td>\n",
       "      <td>121569.0</td>\n",
       "      <td>20130320T012845.190374_42.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.03</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1</td>\n",
       "      <td>281.67</td>\n",
       "      <td>111.67</td>\n",
       "      <td>{}</td>\n",
       "      <td>121569.0</td>\n",
       "      <td>20130320T012845.190374_42.png</td>\n",
       "      <td>1</td>\n",
       "      <td>14.53</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2</td>\n",
       "      <td>230.28</td>\n",
       "      <td>91.67</td>\n",
       "      <td>{}</td>\n",
       "      <td>121569.0</td>\n",
       "      <td>20130320T012845.190374_42.png</td>\n",
       "      <td>1</td>\n",
       "      <td>15.92</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3</td>\n",
       "      <td>205.28</td>\n",
       "      <td>1.11</td>\n",
       "      <td>{}</td>\n",
       "      <td>121569.0</td>\n",
       "      <td>20130320T012845.190374_42.png</td>\n",
       "      <td>1</td>\n",
       "      <td>15.92</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "      <td>23.89</td>\n",
       "      <td>176.67</td>\n",
       "      <td>{}</td>\n",
       "      <td>56319.0</td>\n",
       "      <td>20130320T005544.578414.Cam6_22.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.98</td>\n",
       "      <td>{}</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [42, 42, 4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>6.94</td>\n",
       "      <td>138.89</td>\n",
       "      <td>{}</td>\n",
       "      <td>56319.0</td>\n",
       "      <td>20130320T005544.578414.Cam6_22.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.59</td>\n",
       "      <td>{}</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [24, 24, 2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2</td>\n",
       "      <td>75.28</td>\n",
       "      <td>130.00</td>\n",
       "      <td>{}</td>\n",
       "      <td>56319.0</td>\n",
       "      <td>20130320T005544.578414.Cam6_22.png</td>\n",
       "      <td>1</td>\n",
       "      <td>19.53</td>\n",
       "      <td>{}</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [94, 94, 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>3</td>\n",
       "      <td>56.39</td>\n",
       "      <td>201.11</td>\n",
       "      <td>{}</td>\n",
       "      <td>56319.0</td>\n",
       "      <td>20130320T005544.578414.Cam6_22.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.70</td>\n",
       "      <td>{}</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [75, 75, 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>4</td>\n",
       "      <td>69.72</td>\n",
       "      <td>149.17</td>\n",
       "      <td>{}</td>\n",
       "      <td>56319.0</td>\n",
       "      <td>20130320T005544.578414.Cam6_22.png</td>\n",
       "      <td>1</td>\n",
       "      <td>16.75</td>\n",
       "      <td>{}</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [86, 86, 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0</td>\n",
       "      <td>63.61</td>\n",
       "      <td>176.39</td>\n",
       "      <td>{}</td>\n",
       "      <td>94637.0</td>\n",
       "      <td>20130320T005553.530973.Cam6_13.png</td>\n",
       "      <td>1</td>\n",
       "      <td>24.81</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [88, 88, 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1</td>\n",
       "      <td>79.17</td>\n",
       "      <td>154.44</td>\n",
       "      <td>{}</td>\n",
       "      <td>94637.0</td>\n",
       "      <td>20130320T005553.530973.Cam6_13.png</td>\n",
       "      <td>1</td>\n",
       "      <td>23.42</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [102, 102,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2</td>\n",
       "      <td>30.00</td>\n",
       "      <td>96.11</td>\n",
       "      <td>{}</td>\n",
       "      <td>94637.0</td>\n",
       "      <td>20130320T005553.530973.Cam6_13.png</td>\n",
       "      <td>1</td>\n",
       "      <td>23.42</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [53, 53, 5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>3</td>\n",
       "      <td>64.44</td>\n",
       "      <td>99.44</td>\n",
       "      <td>{}</td>\n",
       "      <td>94637.0</td>\n",
       "      <td>20130320T005553.530973.Cam6_13.png</td>\n",
       "      <td>1</td>\n",
       "      <td>28.98</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [93, 93, 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>4</td>\n",
       "      <td>114.17</td>\n",
       "      <td>80.83</td>\n",
       "      <td>{}</td>\n",
       "      <td>94637.0</td>\n",
       "      <td>20130320T005553.530973.Cam6_13.png</td>\n",
       "      <td>1</td>\n",
       "      <td>27.59</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [141, 141,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>5</td>\n",
       "      <td>78.06</td>\n",
       "      <td>44.44</td>\n",
       "      <td>{}</td>\n",
       "      <td>94637.0</td>\n",
       "      <td>20130320T005553.530973.Cam6_13.png</td>\n",
       "      <td>1</td>\n",
       "      <td>27.59</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [105, 105,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0</td>\n",
       "      <td>74.72</td>\n",
       "      <td>190.83</td>\n",
       "      <td>{}</td>\n",
       "      <td>118393.0</td>\n",
       "      <td>20130320T005617.912359.Cam6_63.png</td>\n",
       "      <td>1</td>\n",
       "      <td>15.09</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [89, 89, 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1</td>\n",
       "      <td>161.39</td>\n",
       "      <td>43.61</td>\n",
       "      <td>{}</td>\n",
       "      <td>118393.0</td>\n",
       "      <td>20130320T005617.912359.Cam6_63.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.03</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [178, 178,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2</td>\n",
       "      <td>212.50</td>\n",
       "      <td>44.44</td>\n",
       "      <td>{}</td>\n",
       "      <td>118393.0</td>\n",
       "      <td>20130320T005617.912359.Cam6_63.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.87</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>3</td>\n",
       "      <td>286.11</td>\n",
       "      <td>30.28</td>\n",
       "      <td>{}</td>\n",
       "      <td>118393.0</td>\n",
       "      <td>20130320T005617.912359.Cam6_63.png</td>\n",
       "      <td>1</td>\n",
       "      <td>19.53</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4647</th>\n",
       "      <td>13</td>\n",
       "      <td>281.11</td>\n",
       "      <td>23.61</td>\n",
       "      <td>{}</td>\n",
       "      <td>101898.0</td>\n",
       "      <td>20130320T012911.476656_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>16.48</td>\n",
       "      <td>{}</td>\n",
       "      <td>17.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4648</th>\n",
       "      <td>14</td>\n",
       "      <td>303.89</td>\n",
       "      <td>46.39</td>\n",
       "      <td>{}</td>\n",
       "      <td>101898.0</td>\n",
       "      <td>20130320T012911.476656_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>16.48</td>\n",
       "      <td>{}</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4649</th>\n",
       "      <td>15</td>\n",
       "      <td>263.89</td>\n",
       "      <td>5.56</td>\n",
       "      <td>{}</td>\n",
       "      <td>101898.0</td>\n",
       "      <td>20130320T012911.476656_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>16.48</td>\n",
       "      <td>{}</td>\n",
       "      <td>17.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4650</th>\n",
       "      <td>16</td>\n",
       "      <td>49.44</td>\n",
       "      <td>125.28</td>\n",
       "      <td>{}</td>\n",
       "      <td>101898.0</td>\n",
       "      <td>20130320T012911.476656_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>14.53</td>\n",
       "      <td>{}</td>\n",
       "      <td>17.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [63, 63, 6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4651</th>\n",
       "      <td>0</td>\n",
       "      <td>90.54</td>\n",
       "      <td>110.54</td>\n",
       "      <td>{}</td>\n",
       "      <td>50471.0</td>\n",
       "      <td>20130320T004531.613372.Cam6_24.png</td>\n",
       "      <td>1</td>\n",
       "      <td>19.61</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [110, 110,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4652</th>\n",
       "      <td>1</td>\n",
       "      <td>97.30</td>\n",
       "      <td>79.73</td>\n",
       "      <td>{}</td>\n",
       "      <td>50471.0</td>\n",
       "      <td>20130320T004531.613372.Cam6_24.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.53</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [115, 115,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4653</th>\n",
       "      <td>2</td>\n",
       "      <td>99.73</td>\n",
       "      <td>64.32</td>\n",
       "      <td>{}</td>\n",
       "      <td>50471.0</td>\n",
       "      <td>20130320T004531.613372.Cam6_24.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.53</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [118, 118,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4654</th>\n",
       "      <td>3</td>\n",
       "      <td>64.32</td>\n",
       "      <td>49.46</td>\n",
       "      <td>{}</td>\n",
       "      <td>50471.0</td>\n",
       "      <td>20130320T004531.613372.Cam6_24.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.15</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [84, 84, 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4655</th>\n",
       "      <td>4</td>\n",
       "      <td>38.92</td>\n",
       "      <td>70.27</td>\n",
       "      <td>{}</td>\n",
       "      <td>50471.0</td>\n",
       "      <td>20130320T004531.613372.Cam6_24.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.80</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [57, 57, 5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4656</th>\n",
       "      <td>5</td>\n",
       "      <td>55.41</td>\n",
       "      <td>94.86</td>\n",
       "      <td>{}</td>\n",
       "      <td>50471.0</td>\n",
       "      <td>20130320T004531.613372.Cam6_24.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.80</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [74, 74, 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4657</th>\n",
       "      <td>0</td>\n",
       "      <td>45.56</td>\n",
       "      <td>186.11</td>\n",
       "      <td>{}</td>\n",
       "      <td>63334.0</td>\n",
       "      <td>20130320T013610.151823_23.png</td>\n",
       "      <td>1</td>\n",
       "      <td>14.81</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [60, 60, 6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4658</th>\n",
       "      <td>1</td>\n",
       "      <td>59.72</td>\n",
       "      <td>189.72</td>\n",
       "      <td>{}</td>\n",
       "      <td>63334.0</td>\n",
       "      <td>20130320T013610.151823_23.png</td>\n",
       "      <td>1</td>\n",
       "      <td>14.81</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [74, 74, 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4659</th>\n",
       "      <td>2</td>\n",
       "      <td>45.56</td>\n",
       "      <td>113.61</td>\n",
       "      <td>{}</td>\n",
       "      <td>63334.0</td>\n",
       "      <td>20130320T013610.151823_23.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.03</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [62, 62, 6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4660</th>\n",
       "      <td>3</td>\n",
       "      <td>48.89</td>\n",
       "      <td>60.28</td>\n",
       "      <td>{}</td>\n",
       "      <td>63334.0</td>\n",
       "      <td>20130320T013610.151823_23.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.70</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [67, 67, 6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4661</th>\n",
       "      <td>4</td>\n",
       "      <td>191.94</td>\n",
       "      <td>77.22</td>\n",
       "      <td>{}</td>\n",
       "      <td>63334.0</td>\n",
       "      <td>20130320T013610.151823_23.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.87</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4662</th>\n",
       "      <td>5</td>\n",
       "      <td>251.67</td>\n",
       "      <td>99.17</td>\n",
       "      <td>{}</td>\n",
       "      <td>63334.0</td>\n",
       "      <td>20130320T013610.151823_23.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.03</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4663</th>\n",
       "      <td>0</td>\n",
       "      <td>123.08</td>\n",
       "      <td>128.08</td>\n",
       "      <td>{}</td>\n",
       "      <td>86698.0</td>\n",
       "      <td>20130320T004724.568099.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>24.50</td>\n",
       "      <td>{}</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [147, 147,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4664</th>\n",
       "      <td>1</td>\n",
       "      <td>131.54</td>\n",
       "      <td>156.92</td>\n",
       "      <td>{}</td>\n",
       "      <td>86698.0</td>\n",
       "      <td>20130320T004724.568099.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>24.50</td>\n",
       "      <td>{}</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [156, 155,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4665</th>\n",
       "      <td>2</td>\n",
       "      <td>168.08</td>\n",
       "      <td>144.62</td>\n",
       "      <td>{}</td>\n",
       "      <td>86698.0</td>\n",
       "      <td>20130320T004724.568099.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>24.50</td>\n",
       "      <td>{}</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [192, 192,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4666</th>\n",
       "      <td>3</td>\n",
       "      <td>219.62</td>\n",
       "      <td>150.38</td>\n",
       "      <td>{}</td>\n",
       "      <td>86698.0</td>\n",
       "      <td>20130320T004724.568099.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>22.19</td>\n",
       "      <td>{}</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4667</th>\n",
       "      <td>4</td>\n",
       "      <td>259.62</td>\n",
       "      <td>73.46</td>\n",
       "      <td>{}</td>\n",
       "      <td>86698.0</td>\n",
       "      <td>20130320T004724.568099.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>19.88</td>\n",
       "      <td>{}</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4668</th>\n",
       "      <td>5</td>\n",
       "      <td>286.15</td>\n",
       "      <td>53.08</td>\n",
       "      <td>{}</td>\n",
       "      <td>86698.0</td>\n",
       "      <td>20130320T004724.568099.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>19.88</td>\n",
       "      <td>{}</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4669</th>\n",
       "      <td>6</td>\n",
       "      <td>296.15</td>\n",
       "      <td>92.69</td>\n",
       "      <td>{}</td>\n",
       "      <td>86698.0</td>\n",
       "      <td>20130320T004724.568099.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>19.88</td>\n",
       "      <td>{}</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4670</th>\n",
       "      <td>7</td>\n",
       "      <td>272.69</td>\n",
       "      <td>18.08</td>\n",
       "      <td>{}</td>\n",
       "      <td>86698.0</td>\n",
       "      <td>20130320T004724.568099.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>19.88</td>\n",
       "      <td>{}</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4671</th>\n",
       "      <td>8</td>\n",
       "      <td>239.23</td>\n",
       "      <td>28.08</td>\n",
       "      <td>{}</td>\n",
       "      <td>86698.0</td>\n",
       "      <td>20130320T004724.568099.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>19.88</td>\n",
       "      <td>{}</td>\n",
       "      <td>10.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4672</th>\n",
       "      <td>9</td>\n",
       "      <td>298.85</td>\n",
       "      <td>34.62</td>\n",
       "      <td>{}</td>\n",
       "      <td>86698.0</td>\n",
       "      <td>20130320T004724.568099.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.96</td>\n",
       "      <td>{}</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4673</th>\n",
       "      <td>0</td>\n",
       "      <td>133.44</td>\n",
       "      <td>92.81</td>\n",
       "      <td>{}</td>\n",
       "      <td>111762.0</td>\n",
       "      <td>20130320T004412.183109.Cam6_51.png</td>\n",
       "      <td>1</td>\n",
       "      <td>15.95</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [149, 149,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4674</th>\n",
       "      <td>1</td>\n",
       "      <td>125.31</td>\n",
       "      <td>120.31</td>\n",
       "      <td>{}</td>\n",
       "      <td>111762.0</td>\n",
       "      <td>20130320T004412.183109.Cam6_51.png</td>\n",
       "      <td>1</td>\n",
       "      <td>15.95</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [141, 141,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4675</th>\n",
       "      <td>2</td>\n",
       "      <td>27.19</td>\n",
       "      <td>120.00</td>\n",
       "      <td>{}</td>\n",
       "      <td>111762.0</td>\n",
       "      <td>20130320T004412.183109.Cam6_51.png</td>\n",
       "      <td>1</td>\n",
       "      <td>14.70</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [41, 41, 4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4676</th>\n",
       "      <td>3</td>\n",
       "      <td>3.44</td>\n",
       "      <td>115.94</td>\n",
       "      <td>{}</td>\n",
       "      <td>111762.0</td>\n",
       "      <td>20130320T004412.183109.Cam6_51.png</td>\n",
       "      <td>1</td>\n",
       "      <td>13.45</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [16, 16, 1...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4677 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     #item     c-x     c-y file_attributes  file_size  \\\n",
       "0        0  170.62  159.69              {}    98334.0   \n",
       "1        0  195.81  110.00              {}   108751.0   \n",
       "2        1  216.13  124.19              {}   108751.0   \n",
       "3        2  295.81   89.35              {}   108751.0   \n",
       "4        0   87.50   62.22              {}   120851.0   \n",
       "5        1  101.67    7.22              {}   120851.0   \n",
       "6        2    3.33  168.89              {}   120851.0   \n",
       "7        3   35.28  165.83              {}   120851.0   \n",
       "8        0  151.94   13.87              {}   103340.0   \n",
       "9        1  140.00   30.97              {}   103340.0   \n",
       "10       2  197.10  147.10              {}   103340.0   \n",
       "11       0  261.11  105.83              {}   121569.0   \n",
       "12       1  281.67  111.67              {}   121569.0   \n",
       "13       2  230.28   91.67              {}   121569.0   \n",
       "14       3  205.28    1.11              {}   121569.0   \n",
       "15       0   23.89  176.67              {}    56319.0   \n",
       "16       1    6.94  138.89              {}    56319.0   \n",
       "17       2   75.28  130.00              {}    56319.0   \n",
       "18       3   56.39  201.11              {}    56319.0   \n",
       "19       4   69.72  149.17              {}    56319.0   \n",
       "20       0   63.61  176.39              {}    94637.0   \n",
       "21       1   79.17  154.44              {}    94637.0   \n",
       "22       2   30.00   96.11              {}    94637.0   \n",
       "23       3   64.44   99.44              {}    94637.0   \n",
       "24       4  114.17   80.83              {}    94637.0   \n",
       "25       5   78.06   44.44              {}    94637.0   \n",
       "26       0   74.72  190.83              {}   118393.0   \n",
       "27       1  161.39   43.61              {}   118393.0   \n",
       "28       2  212.50   44.44              {}   118393.0   \n",
       "29       3  286.11   30.28              {}   118393.0   \n",
       "...    ...     ...     ...             ...        ...   \n",
       "4647    13  281.11   23.61              {}   101898.0   \n",
       "4648    14  303.89   46.39              {}   101898.0   \n",
       "4649    15  263.89    5.56              {}   101898.0   \n",
       "4650    16   49.44  125.28              {}   101898.0   \n",
       "4651     0   90.54  110.54              {}    50471.0   \n",
       "4652     1   97.30   79.73              {}    50471.0   \n",
       "4653     2   99.73   64.32              {}    50471.0   \n",
       "4654     3   64.32   49.46              {}    50471.0   \n",
       "4655     4   38.92   70.27              {}    50471.0   \n",
       "4656     5   55.41   94.86              {}    50471.0   \n",
       "4657     0   45.56  186.11              {}    63334.0   \n",
       "4658     1   59.72  189.72              {}    63334.0   \n",
       "4659     2   45.56  113.61              {}    63334.0   \n",
       "4660     3   48.89   60.28              {}    63334.0   \n",
       "4661     4  191.94   77.22              {}    63334.0   \n",
       "4662     5  251.67   99.17              {}    63334.0   \n",
       "4663     0  123.08  128.08              {}    86698.0   \n",
       "4664     1  131.54  156.92              {}    86698.0   \n",
       "4665     2  168.08  144.62              {}    86698.0   \n",
       "4666     3  219.62  150.38              {}    86698.0   \n",
       "4667     4  259.62   73.46              {}    86698.0   \n",
       "4668     5  286.15   53.08              {}    86698.0   \n",
       "4669     6  296.15   92.69              {}    86698.0   \n",
       "4670     7  272.69   18.08              {}    86698.0   \n",
       "4671     8  239.23   28.08              {}    86698.0   \n",
       "4672     9  298.85   34.62              {}    86698.0   \n",
       "4673     0  133.44   92.81              {}   111762.0   \n",
       "4674     1  125.31  120.31              {}   111762.0   \n",
       "4675     2   27.19  120.00              {}   111762.0   \n",
       "4676     3    3.44  115.94              {}   111762.0   \n",
       "\n",
       "                                filename label  radius region_attributes  \\\n",
       "0     20130320T004403.421053.Cam6_32.png     1   24.39                {}   \n",
       "1     20130320T005044.762746.Cam6_62.png     1   13.87                {}   \n",
       "2     20130320T005044.762746.Cam6_62.png     1   15.16                {}   \n",
       "3     20130320T005044.762746.Cam6_62.png     1   11.29                {}   \n",
       "4     20130320T005748.390478.Cam6_53.png     1   20.09                {}   \n",
       "5     20130320T005748.390478.Cam6_53.png     1   16.48                {}   \n",
       "6     20130320T005748.390478.Cam6_53.png     1   16.48                {}   \n",
       "7     20130320T005748.390478.Cam6_53.png     1   16.48                {}   \n",
       "8     20130320T004928.380174.Cam6_52.png     1   20.64                {}   \n",
       "9     20130320T004928.380174.Cam6_52.png     1   20.64                {}   \n",
       "10    20130320T004928.380174.Cam6_52.png     1   17.74                {}   \n",
       "11         20130320T012845.190374_42.png     1   17.03                {}   \n",
       "12         20130320T012845.190374_42.png     1   14.53                {}   \n",
       "13         20130320T012845.190374_42.png     1   15.92                {}   \n",
       "14         20130320T012845.190374_42.png     1   15.92                {}   \n",
       "15    20130320T005544.578414.Cam6_22.png     1   18.98                {}   \n",
       "16    20130320T005544.578414.Cam6_22.png     1   17.59                {}   \n",
       "17    20130320T005544.578414.Cam6_22.png     1   19.53                {}   \n",
       "18    20130320T005544.578414.Cam6_22.png     1   18.70                {}   \n",
       "19    20130320T005544.578414.Cam6_22.png     1   16.75                {}   \n",
       "20    20130320T005553.530973.Cam6_13.png     1   24.81                {}   \n",
       "21    20130320T005553.530973.Cam6_13.png     1   23.42                {}   \n",
       "22    20130320T005553.530973.Cam6_13.png     1   23.42                {}   \n",
       "23    20130320T005553.530973.Cam6_13.png     1   28.98                {}   \n",
       "24    20130320T005553.530973.Cam6_13.png     1   27.59                {}   \n",
       "25    20130320T005553.530973.Cam6_13.png     1   27.59                {}   \n",
       "26    20130320T005617.912359.Cam6_63.png     1   15.09                {}   \n",
       "27    20130320T005617.912359.Cam6_63.png     1   17.03                {}   \n",
       "28    20130320T005617.912359.Cam6_63.png     1   17.87                {}   \n",
       "29    20130320T005617.912359.Cam6_63.png     1   19.53                {}   \n",
       "...                                  ...   ...     ...               ...   \n",
       "4647       20130320T012911.476656_21.png     1   16.48                {}   \n",
       "4648       20130320T012911.476656_21.png     1   16.48                {}   \n",
       "4649       20130320T012911.476656_21.png     1   16.48                {}   \n",
       "4650       20130320T012911.476656_21.png     1   14.53                {}   \n",
       "4651  20130320T004531.613372.Cam6_24.png     1   19.61                {}   \n",
       "4652  20130320T004531.613372.Cam6_24.png     1   18.53                {}   \n",
       "4653  20130320T004531.613372.Cam6_24.png     1   18.53                {}   \n",
       "4654  20130320T004531.613372.Cam6_24.png     1   20.15                {}   \n",
       "4655  20130320T004531.613372.Cam6_24.png     1   18.80                {}   \n",
       "4656  20130320T004531.613372.Cam6_24.png     1   18.80                {}   \n",
       "4657       20130320T013610.151823_23.png     1   14.81                {}   \n",
       "4658       20130320T013610.151823_23.png     1   14.81                {}   \n",
       "4659       20130320T013610.151823_23.png     1   17.03                {}   \n",
       "4660       20130320T013610.151823_23.png     1   18.70                {}   \n",
       "4661       20130320T013610.151823_23.png     1   17.87                {}   \n",
       "4662       20130320T013610.151823_23.png     1   17.03                {}   \n",
       "4663  20130320T004724.568099.Cam6_21.png     1   24.50                {}   \n",
       "4664  20130320T004724.568099.Cam6_21.png     1   24.50                {}   \n",
       "4665  20130320T004724.568099.Cam6_21.png     1   24.50                {}   \n",
       "4666  20130320T004724.568099.Cam6_21.png     1   22.19                {}   \n",
       "4667  20130320T004724.568099.Cam6_21.png     1   19.88                {}   \n",
       "4668  20130320T004724.568099.Cam6_21.png     1   19.88                {}   \n",
       "4669  20130320T004724.568099.Cam6_21.png     1   19.88                {}   \n",
       "4670  20130320T004724.568099.Cam6_21.png     1   19.88                {}   \n",
       "4671  20130320T004724.568099.Cam6_21.png     1   19.88                {}   \n",
       "4672  20130320T004724.568099.Cam6_21.png     1   17.96                {}   \n",
       "4673  20130320T004412.183109.Cam6_51.png     1   15.95                {}   \n",
       "4674  20130320T004412.183109.Cam6_51.png     1   15.95                {}   \n",
       "4675  20130320T004412.183109.Cam6_51.png     1   14.70                {}   \n",
       "4676  20130320T004412.183109.Cam6_51.png     1   13.45                {}   \n",
       "\n",
       "      region_count  region_id  \\\n",
       "0              1.0        0.0   \n",
       "1              3.0        0.0   \n",
       "2              3.0        1.0   \n",
       "3              3.0        2.0   \n",
       "4              4.0        0.0   \n",
       "5              4.0        1.0   \n",
       "6              4.0        2.0   \n",
       "7              4.0        3.0   \n",
       "8              3.0        0.0   \n",
       "9              3.0        1.0   \n",
       "10             3.0        2.0   \n",
       "11             4.0        0.0   \n",
       "12             4.0        1.0   \n",
       "13             4.0        2.0   \n",
       "14             4.0        3.0   \n",
       "15             5.0        0.0   \n",
       "16             5.0        1.0   \n",
       "17             5.0        2.0   \n",
       "18             5.0        3.0   \n",
       "19             5.0        4.0   \n",
       "20             6.0        0.0   \n",
       "21             6.0        1.0   \n",
       "22             6.0        2.0   \n",
       "23             6.0        3.0   \n",
       "24             6.0        4.0   \n",
       "25             6.0        5.0   \n",
       "26             4.0        0.0   \n",
       "27             4.0        1.0   \n",
       "28             4.0        2.0   \n",
       "29             4.0        3.0   \n",
       "...            ...        ...   \n",
       "4647          17.0       13.0   \n",
       "4648          17.0       14.0   \n",
       "4649          17.0       15.0   \n",
       "4650          17.0       16.0   \n",
       "4651           6.0        0.0   \n",
       "4652           6.0        1.0   \n",
       "4653           6.0        2.0   \n",
       "4654           6.0        3.0   \n",
       "4655           6.0        4.0   \n",
       "4656           6.0        5.0   \n",
       "4657           6.0        0.0   \n",
       "4658           6.0        1.0   \n",
       "4659           6.0        2.0   \n",
       "4660           6.0        3.0   \n",
       "4661           6.0        4.0   \n",
       "4662           6.0        5.0   \n",
       "4663          10.0        0.0   \n",
       "4664          10.0        1.0   \n",
       "4665          10.0        2.0   \n",
       "4666          10.0        3.0   \n",
       "4667          10.0        4.0   \n",
       "4668          10.0        5.0   \n",
       "4669          10.0        6.0   \n",
       "4670          10.0        7.0   \n",
       "4671          10.0        8.0   \n",
       "4672          10.0        9.0   \n",
       "4673           4.0        0.0   \n",
       "4674           4.0        1.0   \n",
       "4675           4.0        2.0   \n",
       "4676           4.0        3.0   \n",
       "\n",
       "                                region_shape_attributes  \n",
       "0     {'name': 'polygon', 'all_points_x': [195, 194,...  \n",
       "1     {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "2     {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "3     {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4     {'name': 'polygon', 'all_points_x': [107, 107,...  \n",
       "5     {'name': 'polygon', 'all_points_x': [118, 118,...  \n",
       "6     {'name': 'polygon', 'all_points_x': [19, 19, 1...  \n",
       "7     {'name': 'polygon', 'all_points_x': [51, 51, 5...  \n",
       "8     {'name': 'polygon', 'all_points_x': [172, 172,...  \n",
       "9     {'name': 'polygon', 'all_points_x': [160, 160,...  \n",
       "10    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "11    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "12    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "13    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "14    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "15    {'name': 'polygon', 'all_points_x': [42, 42, 4...  \n",
       "16    {'name': 'polygon', 'all_points_x': [24, 24, 2...  \n",
       "17    {'name': 'polygon', 'all_points_x': [94, 94, 9...  \n",
       "18    {'name': 'polygon', 'all_points_x': [75, 75, 7...  \n",
       "19    {'name': 'polygon', 'all_points_x': [86, 86, 8...  \n",
       "20    {'name': 'polygon', 'all_points_x': [88, 88, 8...  \n",
       "21    {'name': 'polygon', 'all_points_x': [102, 102,...  \n",
       "22    {'name': 'polygon', 'all_points_x': [53, 53, 5...  \n",
       "23    {'name': 'polygon', 'all_points_x': [93, 93, 9...  \n",
       "24    {'name': 'polygon', 'all_points_x': [141, 141,...  \n",
       "25    {'name': 'polygon', 'all_points_x': [105, 105,...  \n",
       "26    {'name': 'polygon', 'all_points_x': [89, 89, 8...  \n",
       "27    {'name': 'polygon', 'all_points_x': [178, 178,...  \n",
       "28    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "29    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "...                                                 ...  \n",
       "4647  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4648  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4649  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4650  {'name': 'polygon', 'all_points_x': [63, 63, 6...  \n",
       "4651  {'name': 'polygon', 'all_points_x': [110, 110,...  \n",
       "4652  {'name': 'polygon', 'all_points_x': [115, 115,...  \n",
       "4653  {'name': 'polygon', 'all_points_x': [118, 118,...  \n",
       "4654  {'name': 'polygon', 'all_points_x': [84, 84, 8...  \n",
       "4655  {'name': 'polygon', 'all_points_x': [57, 57, 5...  \n",
       "4656  {'name': 'polygon', 'all_points_x': [74, 74, 7...  \n",
       "4657  {'name': 'polygon', 'all_points_x': [60, 60, 6...  \n",
       "4658  {'name': 'polygon', 'all_points_x': [74, 74, 7...  \n",
       "4659  {'name': 'polygon', 'all_points_x': [62, 62, 6...  \n",
       "4660  {'name': 'polygon', 'all_points_x': [67, 67, 6...  \n",
       "4661  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4662  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4663  {'name': 'polygon', 'all_points_x': [147, 147,...  \n",
       "4664  {'name': 'polygon', 'all_points_x': [156, 155,...  \n",
       "4665  {'name': 'polygon', 'all_points_x': [192, 192,...  \n",
       "4666  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4667  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4668  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4669  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4670  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4671  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4672  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4673  {'name': 'polygon', 'all_points_x': [149, 149,...  \n",
       "4674  {'name': 'polygon', 'all_points_x': [141, 141,...  \n",
       "4675  {'name': 'polygon', 'all_points_x': [41, 41, 4...  \n",
       "4676  {'name': 'polygon', 'all_points_x': [16, 16, 1...  \n",
       "\n",
       "[4677 rows x 12 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LOOP THROUGH ALL IMAGES ON TEST SET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kiprono/.local/lib/python3.7/site-packages/ipykernel_launcher.py:26: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
      "of pandas will change to not sort by default.\n",
      "\n",
      "To accept the future behavior, pass 'sort=False'.\n",
      "\n",
      "To retain the current behavior and silence the warning, pass 'sort=True'.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "metadf_apples = pd.DataFrame(columns=['#item', 'c-x', 'c-y', 'radius', 'label', 'filename', 'file_size',\n",
    "       'file_attributes', 'region_count', 'region_id',\n",
    "       'region_shape_attributes', 'region_attributes'])\n",
    "\n",
    "apples = os.path.join(os.getcwd(),\"test_csv\")\n",
    "apples_images = os.path.join(os.getcwd(),\"test_images\")\n",
    "filesList = os.listdir(apples)\n",
    "for index,files in enumerate(filesList):\n",
    "    file_path = os.path.join(apples,files)\n",
    "    df = pd.read_csv(file_path)\n",
    "    image_name = files.replace(\".csv\",\".png\")\n",
    "    for row in range(len(df)):\n",
    "        df.at[row,\"filename\"] = image_name\n",
    "        img = cv.imread(os.path.join(apples_images,image_name))\n",
    "        df.at[row,\"file_size\"] = Path(os.path.join(apples_images,image_name)).stat().st_size\n",
    "        df.at[row,\"file_attributes\"] = '{}'\n",
    "        df.at[row,\"region_count\"] = len(df)\n",
    "        df.at[row,'region_id'] = row\n",
    "        t = {\"name\":\"polygon\",\"all_points_x\":None,\"all_points_y\":None}\n",
    "        x,y = xy_values(df.at[row,\"c-x\"],df.at[row,\"c-y\"],df.at[row,\"radius\"],img.shape[0],img.shape[1])\n",
    "        t['all_points_x']  = x\n",
    "        t['all_points_y'] = y\n",
    "        df.at[row,'region_shape_attributes'] = object()\n",
    "        df.at[row,'region_shape_attributes'] = t\n",
    "        df.at[row,\"region_attributes\"] = '{}'\n",
    "    metadf_apple = pd.concat([metadf_apples, df], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#item</th>\n",
       "      <th>c-x</th>\n",
       "      <th>c-y</th>\n",
       "      <th>file_attributes</th>\n",
       "      <th>file_size</th>\n",
       "      <th>filename</th>\n",
       "      <th>label</th>\n",
       "      <th>radius</th>\n",
       "      <th>region_attributes</th>\n",
       "      <th>region_count</th>\n",
       "      <th>region_id</th>\n",
       "      <th>region_shape_attributes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>66.67</td>\n",
       "      <td>156.39</td>\n",
       "      <td>{}</td>\n",
       "      <td>75957.0</td>\n",
       "      <td>20130320T005809.533784.Cam6_12.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.92</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [87, 87, 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>110.83</td>\n",
       "      <td>149.72</td>\n",
       "      <td>{}</td>\n",
       "      <td>75957.0</td>\n",
       "      <td>20130320T005809.533784.Cam6_12.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.92</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [131, 131,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>118.06</td>\n",
       "      <td>111.94</td>\n",
       "      <td>{}</td>\n",
       "      <td>75957.0</td>\n",
       "      <td>20130320T005809.533784.Cam6_12.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.92</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [138, 138,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>185.28</td>\n",
       "      <td>129.44</td>\n",
       "      <td>{}</td>\n",
       "      <td>75957.0</td>\n",
       "      <td>20130320T005809.533784.Cam6_12.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.92</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>233.61</td>\n",
       "      <td>163.06</td>\n",
       "      <td>{}</td>\n",
       "      <td>75957.0</td>\n",
       "      <td>20130320T005809.533784.Cam6_12.png</td>\n",
       "      <td>1</td>\n",
       "      <td>22.03</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>283.06</td>\n",
       "      <td>191.39</td>\n",
       "      <td>{}</td>\n",
       "      <td>75957.0</td>\n",
       "      <td>20130320T005809.533784.Cam6_12.png</td>\n",
       "      <td>1</td>\n",
       "      <td>23.70</td>\n",
       "      <td>{}</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>18.06</td>\n",
       "      <td>85.56</td>\n",
       "      <td>{}</td>\n",
       "      <td>66960.0</td>\n",
       "      <td>20130320T005732.199644.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.14</td>\n",
       "      <td>{}</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [36, 36, 3...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>99.72</td>\n",
       "      <td>60.83</td>\n",
       "      <td>{}</td>\n",
       "      <td>66960.0</td>\n",
       "      <td>20130320T005732.199644.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.14</td>\n",
       "      <td>{}</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [117, 117,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2</td>\n",
       "      <td>203.89</td>\n",
       "      <td>140.83</td>\n",
       "      <td>{}</td>\n",
       "      <td>66960.0</td>\n",
       "      <td>20130320T005732.199644.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>15.37</td>\n",
       "      <td>{}</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3</td>\n",
       "      <td>170.56</td>\n",
       "      <td>126.67</td>\n",
       "      <td>{}</td>\n",
       "      <td>66960.0</td>\n",
       "      <td>20130320T005732.199644.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.09</td>\n",
       "      <td>{}</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [190, 190,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4</td>\n",
       "      <td>225.00</td>\n",
       "      <td>108.33</td>\n",
       "      <td>{}</td>\n",
       "      <td>66960.0</td>\n",
       "      <td>20130320T005732.199644.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.64</td>\n",
       "      <td>{}</td>\n",
       "      <td>11.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5</td>\n",
       "      <td>175.00</td>\n",
       "      <td>80.28</td>\n",
       "      <td>{}</td>\n",
       "      <td>66960.0</td>\n",
       "      <td>20130320T005732.199644.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.64</td>\n",
       "      <td>{}</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [195, 195,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>6</td>\n",
       "      <td>204.17</td>\n",
       "      <td>56.94</td>\n",
       "      <td>{}</td>\n",
       "      <td>66960.0</td>\n",
       "      <td>20130320T005732.199644.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>23.14</td>\n",
       "      <td>{}</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>7</td>\n",
       "      <td>235.28</td>\n",
       "      <td>58.61</td>\n",
       "      <td>{}</td>\n",
       "      <td>66960.0</td>\n",
       "      <td>20130320T005732.199644.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.42</td>\n",
       "      <td>{}</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>8</td>\n",
       "      <td>207.78</td>\n",
       "      <td>22.78</td>\n",
       "      <td>{}</td>\n",
       "      <td>66960.0</td>\n",
       "      <td>20130320T005732.199644.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>22.03</td>\n",
       "      <td>{}</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>9</td>\n",
       "      <td>183.06</td>\n",
       "      <td>35.00</td>\n",
       "      <td>{}</td>\n",
       "      <td>66960.0</td>\n",
       "      <td>20130320T005732.199644.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.14</td>\n",
       "      <td>{}</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10</td>\n",
       "      <td>191.94</td>\n",
       "      <td>1.67</td>\n",
       "      <td>{}</td>\n",
       "      <td>66960.0</td>\n",
       "      <td>20130320T005732.199644.Cam6_21.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.14</td>\n",
       "      <td>{}</td>\n",
       "      <td>11.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>220.77</td>\n",
       "      <td>98.08</td>\n",
       "      <td>{}</td>\n",
       "      <td>120320.0</td>\n",
       "      <td>20130320T004756.568760.Cam6_41.png</td>\n",
       "      <td>1</td>\n",
       "      <td>19.50</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1</td>\n",
       "      <td>177.69</td>\n",
       "      <td>104.23</td>\n",
       "      <td>{}</td>\n",
       "      <td>120320.0</td>\n",
       "      <td>20130320T004756.568760.Cam6_41.png</td>\n",
       "      <td>1</td>\n",
       "      <td>19.50</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [197, 197,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2</td>\n",
       "      <td>162.69</td>\n",
       "      <td>130.77</td>\n",
       "      <td>{}</td>\n",
       "      <td>120320.0</td>\n",
       "      <td>20130320T004756.568760.Cam6_41.png</td>\n",
       "      <td>1</td>\n",
       "      <td>19.50</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [182, 182,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>3</td>\n",
       "      <td>201.54</td>\n",
       "      <td>160.77</td>\n",
       "      <td>{}</td>\n",
       "      <td>120320.0</td>\n",
       "      <td>20130320T004756.568760.Cam6_41.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.19</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>4</td>\n",
       "      <td>217.31</td>\n",
       "      <td>68.46</td>\n",
       "      <td>{}</td>\n",
       "      <td>120320.0</td>\n",
       "      <td>20130320T004756.568760.Cam6_41.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.19</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>5</td>\n",
       "      <td>242.69</td>\n",
       "      <td>31.15</td>\n",
       "      <td>{}</td>\n",
       "      <td>120320.0</td>\n",
       "      <td>20130320T004756.568760.Cam6_41.png</td>\n",
       "      <td>1</td>\n",
       "      <td>19.50</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>6</td>\n",
       "      <td>214.23</td>\n",
       "      <td>17.69</td>\n",
       "      <td>{}</td>\n",
       "      <td>120320.0</td>\n",
       "      <td>20130320T004756.568760.Cam6_41.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.19</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0</td>\n",
       "      <td>236.45</td>\n",
       "      <td>29.35</td>\n",
       "      <td>{}</td>\n",
       "      <td>93808.0</td>\n",
       "      <td>20130320T005320.384934.Cam6_24.png</td>\n",
       "      <td>1</td>\n",
       "      <td>16.45</td>\n",
       "      <td>{}</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1</td>\n",
       "      <td>140.32</td>\n",
       "      <td>156.77</td>\n",
       "      <td>{}</td>\n",
       "      <td>93808.0</td>\n",
       "      <td>20130320T005320.384934.Cam6_24.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.00</td>\n",
       "      <td>{}</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [160, 160,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2</td>\n",
       "      <td>153.55</td>\n",
       "      <td>149.35</td>\n",
       "      <td>{}</td>\n",
       "      <td>93808.0</td>\n",
       "      <td>20130320T005320.384934.Cam6_24.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.00</td>\n",
       "      <td>{}</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [173, 173,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>3</td>\n",
       "      <td>119.03</td>\n",
       "      <td>185.16</td>\n",
       "      <td>{}</td>\n",
       "      <td>93808.0</td>\n",
       "      <td>20130320T005320.384934.Cam6_24.png</td>\n",
       "      <td>1</td>\n",
       "      <td>21.61</td>\n",
       "      <td>{}</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [140, 140,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>4</td>\n",
       "      <td>159.68</td>\n",
       "      <td>184.84</td>\n",
       "      <td>{}</td>\n",
       "      <td>93808.0</td>\n",
       "      <td>20130320T005320.384934.Cam6_24.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.32</td>\n",
       "      <td>{}</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [180, 179,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0</td>\n",
       "      <td>81.94</td>\n",
       "      <td>38.33</td>\n",
       "      <td>{}</td>\n",
       "      <td>100536.0</td>\n",
       "      <td>20130320T013611.866233_34.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.42</td>\n",
       "      <td>{}</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [100, 100,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1058</th>\n",
       "      <td>4</td>\n",
       "      <td>170.56</td>\n",
       "      <td>175.56</td>\n",
       "      <td>{}</td>\n",
       "      <td>92693.0</td>\n",
       "      <td>20130320T012923.476901_31.png</td>\n",
       "      <td>1</td>\n",
       "      <td>12.59</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [183, 183,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1059</th>\n",
       "      <td>5</td>\n",
       "      <td>78.89</td>\n",
       "      <td>171.11</td>\n",
       "      <td>{}</td>\n",
       "      <td>92693.0</td>\n",
       "      <td>20130320T012923.476901_31.png</td>\n",
       "      <td>1</td>\n",
       "      <td>13.14</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [92, 92, 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1060</th>\n",
       "      <td>6</td>\n",
       "      <td>104.17</td>\n",
       "      <td>182.78</td>\n",
       "      <td>{}</td>\n",
       "      <td>92693.0</td>\n",
       "      <td>20130320T012923.476901_31.png</td>\n",
       "      <td>1</td>\n",
       "      <td>13.14</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [117, 117,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1061</th>\n",
       "      <td>0</td>\n",
       "      <td>50.00</td>\n",
       "      <td>86.22</td>\n",
       "      <td>{}</td>\n",
       "      <td>72067.0</td>\n",
       "      <td>20130320T004530.279967.Cam6_23.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.42</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [70, 70, 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1062</th>\n",
       "      <td>1</td>\n",
       "      <td>81.89</td>\n",
       "      <td>95.41</td>\n",
       "      <td>{}</td>\n",
       "      <td>72067.0</td>\n",
       "      <td>20130320T004530.279967.Cam6_23.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.42</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [102, 102,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1063</th>\n",
       "      <td>2</td>\n",
       "      <td>17.30</td>\n",
       "      <td>27.30</td>\n",
       "      <td>{}</td>\n",
       "      <td>72067.0</td>\n",
       "      <td>20130320T004530.279967.Cam6_23.png</td>\n",
       "      <td>1</td>\n",
       "      <td>16.91</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [34, 34, 3...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1064</th>\n",
       "      <td>0</td>\n",
       "      <td>23.55</td>\n",
       "      <td>156.13</td>\n",
       "      <td>{}</td>\n",
       "      <td>110317.0</td>\n",
       "      <td>20130320T004859.236691.Cam6_43.png</td>\n",
       "      <td>1</td>\n",
       "      <td>39.35</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [62, 62, 6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1065</th>\n",
       "      <td>1</td>\n",
       "      <td>241.94</td>\n",
       "      <td>182.58</td>\n",
       "      <td>{}</td>\n",
       "      <td>110317.0</td>\n",
       "      <td>20130320T004859.236691.Cam6_43.png</td>\n",
       "      <td>1</td>\n",
       "      <td>26.45</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1066</th>\n",
       "      <td>2</td>\n",
       "      <td>117.42</td>\n",
       "      <td>97.42</td>\n",
       "      <td>{}</td>\n",
       "      <td>110317.0</td>\n",
       "      <td>20130320T004859.236691.Cam6_43.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.32</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [137, 137,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1067</th>\n",
       "      <td>3</td>\n",
       "      <td>155.81</td>\n",
       "      <td>99.68</td>\n",
       "      <td>{}</td>\n",
       "      <td>110317.0</td>\n",
       "      <td>20130320T004859.236691.Cam6_43.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.32</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [176, 176,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1068</th>\n",
       "      <td>4</td>\n",
       "      <td>194.52</td>\n",
       "      <td>75.48</td>\n",
       "      <td>{}</td>\n",
       "      <td>110317.0</td>\n",
       "      <td>20130320T004859.236691.Cam6_43.png</td>\n",
       "      <td>1</td>\n",
       "      <td>21.93</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1069</th>\n",
       "      <td>5</td>\n",
       "      <td>235.81</td>\n",
       "      <td>62.26</td>\n",
       "      <td>{}</td>\n",
       "      <td>110317.0</td>\n",
       "      <td>20130320T004859.236691.Cam6_43.png</td>\n",
       "      <td>1</td>\n",
       "      <td>22.58</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1070</th>\n",
       "      <td>6</td>\n",
       "      <td>301.94</td>\n",
       "      <td>76.77</td>\n",
       "      <td>{}</td>\n",
       "      <td>110317.0</td>\n",
       "      <td>20130320T004859.236691.Cam6_43.png</td>\n",
       "      <td>1</td>\n",
       "      <td>22.58</td>\n",
       "      <td>{}</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1071</th>\n",
       "      <td>0</td>\n",
       "      <td>121.25</td>\n",
       "      <td>146.25</td>\n",
       "      <td>{}</td>\n",
       "      <td>129821.0</td>\n",
       "      <td>20130320T004420.945168.Cam6_44.png</td>\n",
       "      <td>1</td>\n",
       "      <td>10.95</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [132, 132,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1072</th>\n",
       "      <td>1</td>\n",
       "      <td>103.75</td>\n",
       "      <td>143.75</td>\n",
       "      <td>{}</td>\n",
       "      <td>129821.0</td>\n",
       "      <td>20130320T004420.945168.Cam6_44.png</td>\n",
       "      <td>1</td>\n",
       "      <td>10.95</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [114, 114,...</td>\n",
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       "    <tr>\n",
       "      <th>1073</th>\n",
       "      <td>2</td>\n",
       "      <td>112.81</td>\n",
       "      <td>164.06</td>\n",
       "      <td>{}</td>\n",
       "      <td>129821.0</td>\n",
       "      <td>20130320T004420.945168.Cam6_44.png</td>\n",
       "      <td>1</td>\n",
       "      <td>10.95</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [123, 123,...</td>\n",
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       "    <tr>\n",
       "      <th>1074</th>\n",
       "      <td>0</td>\n",
       "      <td>198.92</td>\n",
       "      <td>148.65</td>\n",
       "      <td>{}</td>\n",
       "      <td>105723.0</td>\n",
       "      <td>20130320T004534.280053.Cam6_73.png</td>\n",
       "      <td>1</td>\n",
       "      <td>16.64</td>\n",
       "      <td>{}</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
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       "    <tr>\n",
       "      <th>1075</th>\n",
       "      <td>0</td>\n",
       "      <td>115.83</td>\n",
       "      <td>157.78</td>\n",
       "      <td>{}</td>\n",
       "      <td>77818.0</td>\n",
       "      <td>20130320T005801.343117.Cam6_12.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.98</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [134, 134,...</td>\n",
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       "    <tr>\n",
       "      <th>1076</th>\n",
       "      <td>1</td>\n",
       "      <td>163.61</td>\n",
       "      <td>4.72</td>\n",
       "      <td>{}</td>\n",
       "      <td>77818.0</td>\n",
       "      <td>20130320T005801.343117.Cam6_12.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.37</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [183, 183,...</td>\n",
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       "    <tr>\n",
       "      <th>1077</th>\n",
       "      <td>2</td>\n",
       "      <td>236.67</td>\n",
       "      <td>74.72</td>\n",
       "      <td>{}</td>\n",
       "      <td>77818.0</td>\n",
       "      <td>20130320T005801.343117.Cam6_12.png</td>\n",
       "      <td>1</td>\n",
       "      <td>26.20</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
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       "    <tr>\n",
       "      <th>1078</th>\n",
       "      <td>0</td>\n",
       "      <td>125.56</td>\n",
       "      <td>166.67</td>\n",
       "      <td>{}</td>\n",
       "      <td>104791.0</td>\n",
       "      <td>20130320T013550.722937_33.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.37</td>\n",
       "      <td>{}</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>{'name': 'polygon', 'all_points_x': [145, 145,...</td>\n",
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       "    <tr>\n",
       "      <th>1079</th>\n",
       "      <td>1</td>\n",
       "      <td>288.61</td>\n",
       "      <td>12.50</td>\n",
       "      <td>{}</td>\n",
       "      <td>104791.0</td>\n",
       "      <td>20130320T013550.722937_33.png</td>\n",
       "      <td>1</td>\n",
       "      <td>18.98</td>\n",
       "      <td>{}</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
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       "    <tr>\n",
       "      <th>1080</th>\n",
       "      <td>0</td>\n",
       "      <td>60.65</td>\n",
       "      <td>121.94</td>\n",
       "      <td>{}</td>\n",
       "      <td>114437.0</td>\n",
       "      <td>20130320T005329.337492.Cam6_63.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.42</td>\n",
       "      <td>{}</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [78, 78, 7...</td>\n",
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       "    <tr>\n",
       "      <th>1081</th>\n",
       "      <td>1</td>\n",
       "      <td>96.13</td>\n",
       "      <td>115.16</td>\n",
       "      <td>{}</td>\n",
       "      <td>114437.0</td>\n",
       "      <td>20130320T005329.337492.Cam6_63.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.42</td>\n",
       "      <td>{}</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [113, 113,...</td>\n",
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       "    <tr>\n",
       "      <th>1082</th>\n",
       "      <td>2</td>\n",
       "      <td>119.68</td>\n",
       "      <td>103.55</td>\n",
       "      <td>{}</td>\n",
       "      <td>114437.0</td>\n",
       "      <td>20130320T005329.337492.Cam6_63.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.42</td>\n",
       "      <td>{}</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [137, 137,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1083</th>\n",
       "      <td>3</td>\n",
       "      <td>229.03</td>\n",
       "      <td>14.84</td>\n",
       "      <td>{}</td>\n",
       "      <td>114437.0</td>\n",
       "      <td>20130320T005329.337492.Cam6_63.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.42</td>\n",
       "      <td>{}</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1084</th>\n",
       "      <td>4</td>\n",
       "      <td>241.61</td>\n",
       "      <td>2.58</td>\n",
       "      <td>{}</td>\n",
       "      <td>114437.0</td>\n",
       "      <td>20130320T005329.337492.Cam6_63.png</td>\n",
       "      <td>1</td>\n",
       "      <td>17.42</td>\n",
       "      <td>{}</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1085</th>\n",
       "      <td>5</td>\n",
       "      <td>26.13</td>\n",
       "      <td>83.23</td>\n",
       "      <td>{}</td>\n",
       "      <td>114437.0</td>\n",
       "      <td>20130320T005329.337492.Cam6_63.png</td>\n",
       "      <td>1</td>\n",
       "      <td>15.16</td>\n",
       "      <td>{}</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [41, 41, 4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1086</th>\n",
       "      <td>6</td>\n",
       "      <td>10.97</td>\n",
       "      <td>97.74</td>\n",
       "      <td>{}</td>\n",
       "      <td>114437.0</td>\n",
       "      <td>20130320T005329.337492.Cam6_63.png</td>\n",
       "      <td>1</td>\n",
       "      <td>15.16</td>\n",
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       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
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       "    <tr>\n",
       "      <th>1087</th>\n",
       "      <td>7</td>\n",
       "      <td>144.84</td>\n",
       "      <td>17.74</td>\n",
       "      <td>{}</td>\n",
       "      <td>114437.0</td>\n",
       "      <td>20130320T005329.337492.Cam6_63.png</td>\n",
       "      <td>1</td>\n",
       "      <td>16.77</td>\n",
       "      <td>{}</td>\n",
       "      <td>8.0</td>\n",
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       "      <td>{'name': 'polygon', 'all_points_x': [161, 161,...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1088 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     #item     c-x     c-y file_attributes  file_size  \\\n",
       "0        0   66.67  156.39              {}    75957.0   \n",
       "1        1  110.83  149.72              {}    75957.0   \n",
       "2        2  118.06  111.94              {}    75957.0   \n",
       "3        3  185.28  129.44              {}    75957.0   \n",
       "4        4  233.61  163.06              {}    75957.0   \n",
       "5        5  283.06  191.39              {}    75957.0   \n",
       "6        0   18.06   85.56              {}    66960.0   \n",
       "7        1   99.72   60.83              {}    66960.0   \n",
       "8        2  203.89  140.83              {}    66960.0   \n",
       "9        3  170.56  126.67              {}    66960.0   \n",
       "10       4  225.00  108.33              {}    66960.0   \n",
       "11       5  175.00   80.28              {}    66960.0   \n",
       "12       6  204.17   56.94              {}    66960.0   \n",
       "13       7  235.28   58.61              {}    66960.0   \n",
       "14       8  207.78   22.78              {}    66960.0   \n",
       "15       9  183.06   35.00              {}    66960.0   \n",
       "16      10  191.94    1.67              {}    66960.0   \n",
       "17       0  220.77   98.08              {}   120320.0   \n",
       "18       1  177.69  104.23              {}   120320.0   \n",
       "19       2  162.69  130.77              {}   120320.0   \n",
       "20       3  201.54  160.77              {}   120320.0   \n",
       "21       4  217.31   68.46              {}   120320.0   \n",
       "22       5  242.69   31.15              {}   120320.0   \n",
       "23       6  214.23   17.69              {}   120320.0   \n",
       "24       0  236.45   29.35              {}    93808.0   \n",
       "25       1  140.32  156.77              {}    93808.0   \n",
       "26       2  153.55  149.35              {}    93808.0   \n",
       "27       3  119.03  185.16              {}    93808.0   \n",
       "28       4  159.68  184.84              {}    93808.0   \n",
       "29       0   81.94   38.33              {}   100536.0   \n",
       "...    ...     ...     ...             ...        ...   \n",
       "1058     4  170.56  175.56              {}    92693.0   \n",
       "1059     5   78.89  171.11              {}    92693.0   \n",
       "1060     6  104.17  182.78              {}    92693.0   \n",
       "1061     0   50.00   86.22              {}    72067.0   \n",
       "1062     1   81.89   95.41              {}    72067.0   \n",
       "1063     2   17.30   27.30              {}    72067.0   \n",
       "1064     0   23.55  156.13              {}   110317.0   \n",
       "1065     1  241.94  182.58              {}   110317.0   \n",
       "1066     2  117.42   97.42              {}   110317.0   \n",
       "1067     3  155.81   99.68              {}   110317.0   \n",
       "1068     4  194.52   75.48              {}   110317.0   \n",
       "1069     5  235.81   62.26              {}   110317.0   \n",
       "1070     6  301.94   76.77              {}   110317.0   \n",
       "1071     0  121.25  146.25              {}   129821.0   \n",
       "1072     1  103.75  143.75              {}   129821.0   \n",
       "1073     2  112.81  164.06              {}   129821.0   \n",
       "1074     0  198.92  148.65              {}   105723.0   \n",
       "1075     0  115.83  157.78              {}    77818.0   \n",
       "1076     1  163.61    4.72              {}    77818.0   \n",
       "1077     2  236.67   74.72              {}    77818.0   \n",
       "1078     0  125.56  166.67              {}   104791.0   \n",
       "1079     1  288.61   12.50              {}   104791.0   \n",
       "1080     0   60.65  121.94              {}   114437.0   \n",
       "1081     1   96.13  115.16              {}   114437.0   \n",
       "1082     2  119.68  103.55              {}   114437.0   \n",
       "1083     3  229.03   14.84              {}   114437.0   \n",
       "1084     4  241.61    2.58              {}   114437.0   \n",
       "1085     5   26.13   83.23              {}   114437.0   \n",
       "1086     6   10.97   97.74              {}   114437.0   \n",
       "1087     7  144.84   17.74              {}   114437.0   \n",
       "\n",
       "                                filename label  radius region_attributes  \\\n",
       "0     20130320T005809.533784.Cam6_12.png     1   20.92                {}   \n",
       "1     20130320T005809.533784.Cam6_12.png     1   20.92                {}   \n",
       "2     20130320T005809.533784.Cam6_12.png     1   20.92                {}   \n",
       "3     20130320T005809.533784.Cam6_12.png     1   20.92                {}   \n",
       "4     20130320T005809.533784.Cam6_12.png     1   22.03                {}   \n",
       "5     20130320T005809.533784.Cam6_12.png     1   23.70                {}   \n",
       "6     20130320T005732.199644.Cam6_21.png     1   18.14                {}   \n",
       "7     20130320T005732.199644.Cam6_21.png     1   18.14                {}   \n",
       "8     20130320T005732.199644.Cam6_21.png     1   15.37                {}   \n",
       "9     20130320T005732.199644.Cam6_21.png     1   20.09                {}   \n",
       "10    20130320T005732.199644.Cam6_21.png     1   20.64                {}   \n",
       "11    20130320T005732.199644.Cam6_21.png     1   20.64                {}   \n",
       "12    20130320T005732.199644.Cam6_21.png     1   23.14                {}   \n",
       "13    20130320T005732.199644.Cam6_21.png     1   18.42                {}   \n",
       "14    20130320T005732.199644.Cam6_21.png     1   22.03                {}   \n",
       "15    20130320T005732.199644.Cam6_21.png     1   18.14                {}   \n",
       "16    20130320T005732.199644.Cam6_21.png     1   18.14                {}   \n",
       "17    20130320T004756.568760.Cam6_41.png     1   19.50                {}   \n",
       "18    20130320T004756.568760.Cam6_41.png     1   19.50                {}   \n",
       "19    20130320T004756.568760.Cam6_41.png     1   19.50                {}   \n",
       "20    20130320T004756.568760.Cam6_41.png     1   17.19                {}   \n",
       "21    20130320T004756.568760.Cam6_41.png     1   17.19                {}   \n",
       "22    20130320T004756.568760.Cam6_41.png     1   19.50                {}   \n",
       "23    20130320T004756.568760.Cam6_41.png     1   17.19                {}   \n",
       "24    20130320T005320.384934.Cam6_24.png     1   16.45                {}   \n",
       "25    20130320T005320.384934.Cam6_24.png     1   20.00                {}   \n",
       "26    20130320T005320.384934.Cam6_24.png     1   20.00                {}   \n",
       "27    20130320T005320.384934.Cam6_24.png     1   21.61                {}   \n",
       "28    20130320T005320.384934.Cam6_24.png     1   20.32                {}   \n",
       "29         20130320T013611.866233_34.png     1   18.42                {}   \n",
       "...                                  ...   ...     ...               ...   \n",
       "1058       20130320T012923.476901_31.png     1   12.59                {}   \n",
       "1059       20130320T012923.476901_31.png     1   13.14                {}   \n",
       "1060       20130320T012923.476901_31.png     1   13.14                {}   \n",
       "1061  20130320T004530.279967.Cam6_23.png     1   20.42                {}   \n",
       "1062  20130320T004530.279967.Cam6_23.png     1   20.42                {}   \n",
       "1063  20130320T004530.279967.Cam6_23.png     1   16.91                {}   \n",
       "1064  20130320T004859.236691.Cam6_43.png     1   39.35                {}   \n",
       "1065  20130320T004859.236691.Cam6_43.png     1   26.45                {}   \n",
       "1066  20130320T004859.236691.Cam6_43.png     1   20.32                {}   \n",
       "1067  20130320T004859.236691.Cam6_43.png     1   20.32                {}   \n",
       "1068  20130320T004859.236691.Cam6_43.png     1   21.93                {}   \n",
       "1069  20130320T004859.236691.Cam6_43.png     1   22.58                {}   \n",
       "1070  20130320T004859.236691.Cam6_43.png     1   22.58                {}   \n",
       "1071  20130320T004420.945168.Cam6_44.png     1   10.95                {}   \n",
       "1072  20130320T004420.945168.Cam6_44.png     1   10.95                {}   \n",
       "1073  20130320T004420.945168.Cam6_44.png     1   10.95                {}   \n",
       "1074  20130320T004534.280053.Cam6_73.png     1   16.64                {}   \n",
       "1075  20130320T005801.343117.Cam6_12.png     1   18.98                {}   \n",
       "1076  20130320T005801.343117.Cam6_12.png     1   20.37                {}   \n",
       "1077  20130320T005801.343117.Cam6_12.png     1   26.20                {}   \n",
       "1078       20130320T013550.722937_33.png     1   20.37                {}   \n",
       "1079       20130320T013550.722937_33.png     1   18.98                {}   \n",
       "1080  20130320T005329.337492.Cam6_63.png     1   17.42                {}   \n",
       "1081  20130320T005329.337492.Cam6_63.png     1   17.42                {}   \n",
       "1082  20130320T005329.337492.Cam6_63.png     1   17.42                {}   \n",
       "1083  20130320T005329.337492.Cam6_63.png     1   17.42                {}   \n",
       "1084  20130320T005329.337492.Cam6_63.png     1   17.42                {}   \n",
       "1085  20130320T005329.337492.Cam6_63.png     1   15.16                {}   \n",
       "1086  20130320T005329.337492.Cam6_63.png     1   15.16                {}   \n",
       "1087  20130320T005329.337492.Cam6_63.png     1   16.77                {}   \n",
       "\n",
       "      region_count  region_id  \\\n",
       "0              6.0        0.0   \n",
       "1              6.0        1.0   \n",
       "2              6.0        2.0   \n",
       "3              6.0        3.0   \n",
       "4              6.0        4.0   \n",
       "5              6.0        5.0   \n",
       "6             11.0        0.0   \n",
       "7             11.0        1.0   \n",
       "8             11.0        2.0   \n",
       "9             11.0        3.0   \n",
       "10            11.0        4.0   \n",
       "11            11.0        5.0   \n",
       "12            11.0        6.0   \n",
       "13            11.0        7.0   \n",
       "14            11.0        8.0   \n",
       "15            11.0        9.0   \n",
       "16            11.0       10.0   \n",
       "17             7.0        0.0   \n",
       "18             7.0        1.0   \n",
       "19             7.0        2.0   \n",
       "20             7.0        3.0   \n",
       "21             7.0        4.0   \n",
       "22             7.0        5.0   \n",
       "23             7.0        6.0   \n",
       "24             5.0        0.0   \n",
       "25             5.0        1.0   \n",
       "26             5.0        2.0   \n",
       "27             5.0        3.0   \n",
       "28             5.0        4.0   \n",
       "29             2.0        0.0   \n",
       "...            ...        ...   \n",
       "1058           7.0        4.0   \n",
       "1059           7.0        5.0   \n",
       "1060           7.0        6.0   \n",
       "1061           3.0        0.0   \n",
       "1062           3.0        1.0   \n",
       "1063           3.0        2.0   \n",
       "1064           7.0        0.0   \n",
       "1065           7.0        1.0   \n",
       "1066           7.0        2.0   \n",
       "1067           7.0        3.0   \n",
       "1068           7.0        4.0   \n",
       "1069           7.0        5.0   \n",
       "1070           7.0        6.0   \n",
       "1071           3.0        0.0   \n",
       "1072           3.0        1.0   \n",
       "1073           3.0        2.0   \n",
       "1074           1.0        0.0   \n",
       "1075           3.0        0.0   \n",
       "1076           3.0        1.0   \n",
       "1077           3.0        2.0   \n",
       "1078           2.0        0.0   \n",
       "1079           2.0        1.0   \n",
       "1080           8.0        0.0   \n",
       "1081           8.0        1.0   \n",
       "1082           8.0        2.0   \n",
       "1083           8.0        3.0   \n",
       "1084           8.0        4.0   \n",
       "1085           8.0        5.0   \n",
       "1086           8.0        6.0   \n",
       "1087           8.0        7.0   \n",
       "\n",
       "                                region_shape_attributes  \n",
       "0     {'name': 'polygon', 'all_points_x': [87, 87, 8...  \n",
       "1     {'name': 'polygon', 'all_points_x': [131, 131,...  \n",
       "2     {'name': 'polygon', 'all_points_x': [138, 138,...  \n",
       "3     {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4     {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "5     {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "6     {'name': 'polygon', 'all_points_x': [36, 36, 3...  \n",
       "7     {'name': 'polygon', 'all_points_x': [117, 117,...  \n",
       "8     {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "9     {'name': 'polygon', 'all_points_x': [190, 190,...  \n",
       "10    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "11    {'name': 'polygon', 'all_points_x': [195, 195,...  \n",
       "12    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "13    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "14    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "15    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "16    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "17    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "18    {'name': 'polygon', 'all_points_x': [197, 197,...  \n",
       "19    {'name': 'polygon', 'all_points_x': [182, 182,...  \n",
       "20    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "21    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "22    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "23    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "24    {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "25    {'name': 'polygon', 'all_points_x': [160, 160,...  \n",
       "26    {'name': 'polygon', 'all_points_x': [173, 173,...  \n",
       "27    {'name': 'polygon', 'all_points_x': [140, 140,...  \n",
       "28    {'name': 'polygon', 'all_points_x': [180, 179,...  \n",
       "29    {'name': 'polygon', 'all_points_x': [100, 100,...  \n",
       "...                                                 ...  \n",
       "1058  {'name': 'polygon', 'all_points_x': [183, 183,...  \n",
       "1059  {'name': 'polygon', 'all_points_x': [92, 92, 9...  \n",
       "1060  {'name': 'polygon', 'all_points_x': [117, 117,...  \n",
       "1061  {'name': 'polygon', 'all_points_x': [70, 70, 7...  \n",
       "1062  {'name': 'polygon', 'all_points_x': [102, 102,...  \n",
       "1063  {'name': 'polygon', 'all_points_x': [34, 34, 3...  \n",
       "1064  {'name': 'polygon', 'all_points_x': [62, 62, 6...  \n",
       "1065  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "1066  {'name': 'polygon', 'all_points_x': [137, 137,...  \n",
       "1067  {'name': 'polygon', 'all_points_x': [176, 176,...  \n",
       "1068  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "1069  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "1070  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "1071  {'name': 'polygon', 'all_points_x': [132, 132,...  \n",
       "1072  {'name': 'polygon', 'all_points_x': [114, 114,...  \n",
       "1073  {'name': 'polygon', 'all_points_x': [123, 123,...  \n",
       "1074  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "1075  {'name': 'polygon', 'all_points_x': [134, 134,...  \n",
       "1076  {'name': 'polygon', 'all_points_x': [183, 183,...  \n",
       "1077  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "1078  {'name': 'polygon', 'all_points_x': [145, 145,...  \n",
       "1079  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "1080  {'name': 'polygon', 'all_points_x': [78, 78, 7...  \n",
       "1081  {'name': 'polygon', 'all_points_x': [113, 113,...  \n",
       "1082  {'name': 'polygon', 'all_points_x': [137, 137,...  \n",
       "1083  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "1084  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "1085  {'name': 'polygon', 'all_points_x': [41, 41, 4...  \n",
       "1086  {'name': 'polygon', 'all_points_x': [26, 26, 2...  \n",
       "1087  {'name': 'polygon', 'all_points_x': [161, 161,...  \n",
       "\n",
       "[1088 rows x 12 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadf_apples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ROUGH SPACE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Split images and csv annotations into train and test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_images = os.path.join(os.getcwd(),\"images\")\n",
    "all_csv = os.path.join(os.getcwd(),\"annotations_csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#copy train images into train images folder\n",
    "train = random.sample(os.listdir(all_images),int(0.8*1120))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "for image in train:\n",
    "    source_image = os.path.join(os.getcwd(),\"images\",image)\n",
    "    destination_image = os.path.join(os.getcwd(),\"train_images\",image)\n",
    "    shutil.move(source_image,destination_image)\n",
    "    csv_name = image.replace(\".png\",\".csv\")\n",
    "    source_csv = os.path.join(os.getcwd(),\"annotations_csv\",csv_name)\n",
    "    destination_csv = os.path.join(os.getcwd(),\"train_csv\",csv_name)\n",
    "    shutil.move(source_csv,destination_csv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "headers = ['filename', 'file_size', 'file_attributes', 'region_count', 'region_id',\n",
    "       'region_shape_attributes', 'region_attributes']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "apples = \"../Fruits/dataset/apples/dataset/val_csv\"\n",
    "apples_images = \"../Fruits/dataset/apples/dataset/val\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "filesList = os.listdir(apples)\n",
    "file_ = random.choice(filesList)\n",
    "df = pd.read_csv(os.path.join(apples,file_))\n",
    "df\n",
    "image_name = file_.replace(\".csv\",\".png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['filename',\n",
       " 'file_size',\n",
       " 'file_attributes',\n",
       " 'region_count',\n",
       " 'region_id',\n",
       " 'region_shape_attributes',\n",
       " 'region_attributes']"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "['filename', 'file_size', 'file_attributes', 'region_count', 'region_id',\n",
    "       'region_shape_attributes', 'region_attributes']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "#for one csv file\n",
    "for row in range(len(df)):\n",
    "    df.at[row,\"filename\"] = image_name\n",
    "    df.at[row,\"file_size\"] = Path(os.path.join(apples_images,image_name)).stat().st_size\n",
    "    img = cv.imread(os.path.join(apples_images,image_name))\n",
    "    df.at[row,\"file_attributes\"] = '{}'\n",
    "    df.at[row,\"region_count\"] = len(df)\n",
    "    df.at[row,'region_id'] = row\n",
    "    t = {'name':'polygon','all_points_x':None,'all_points_y':None}\n",
    "    x,y = xy_values(df.at[row,\"c-x\"],df.at[row,\"c-y\"],df.at[row,\"radius\"],img.shape[0],img.shape[1])\n",
    "    t['all_points_x']  = x\n",
    "    t['all_points_y'] = y\n",
    "    df.at[row,'region_shape_attributes'] = object()\n",
    "    df.at[row,'region_shape_attributes'] = t\n",
    "    df.at[row,\"region_attributes\"] = '{}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"file_size\"] = df[\"file_size\"].astype(\"int64\")\n",
    "df[\"region_count\"] = df[\"region_count\"].astype(\"int64\")\n",
    "df['region_id'] = df['region_id'].astype(\"int64\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['#item', 'c-x', 'c-y', 'radius', 'label', 'filename', 'file_size',\n",
       "       'file_attributes', 'region_count', 'region_id',\n",
       "       'region_shape_attributes', 'region_attributes'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#item</th>\n",
       "      <th>c-x</th>\n",
       "      <th>c-y</th>\n",
       "      <th>radius</th>\n",
       "      <th>label</th>\n",
       "      <th>filename</th>\n",
       "      <th>file_size</th>\n",
       "      <th>file_attributes</th>\n",
       "      <th>region_count</th>\n",
       "      <th>region_id</th>\n",
       "      <th>region_shape_attributes</th>\n",
       "      <th>region_attributes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>175.48</td>\n",
       "      <td>96.45</td>\n",
       "      <td>24.51</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T004811.616698.Cam6_13.png</td>\n",
       "      <td>92503</td>\n",
       "      <td>{}</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [199, 199,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>164.52</td>\n",
       "      <td>53.87</td>\n",
       "      <td>23.55</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T004811.616698.Cam6_13.png</td>\n",
       "      <td>92503</td>\n",
       "      <td>{}</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [188, 188,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>130.00</td>\n",
       "      <td>30.00</td>\n",
       "      <td>23.55</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T004811.616698.Cam6_13.png</td>\n",
       "      <td>92503</td>\n",
       "      <td>{}</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [153, 153,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>167.10</td>\n",
       "      <td>7.74</td>\n",
       "      <td>23.55</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T004811.616698.Cam6_13.png</td>\n",
       "      <td>92503</td>\n",
       "      <td>{}</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [190, 190,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>196.13</td>\n",
       "      <td>37.42</td>\n",
       "      <td>23.55</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T004811.616698.Cam6_13.png</td>\n",
       "      <td>92503</td>\n",
       "      <td>{}</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>245.48</td>\n",
       "      <td>66.45</td>\n",
       "      <td>23.55</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T004811.616698.Cam6_13.png</td>\n",
       "      <td>92503</td>\n",
       "      <td>{}</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>278.71</td>\n",
       "      <td>48.71</td>\n",
       "      <td>22.90</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T004811.616698.Cam6_13.png</td>\n",
       "      <td>92503</td>\n",
       "      <td>{}</td>\n",
       "      <td>12</td>\n",
       "      <td>6</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>285.16</td>\n",
       "      <td>86.77</td>\n",
       "      <td>23.87</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T004811.616698.Cam6_13.png</td>\n",
       "      <td>92503</td>\n",
       "      <td>{}</td>\n",
       "      <td>12</td>\n",
       "      <td>7</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>266.45</td>\n",
       "      <td>135.81</td>\n",
       "      <td>22.90</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T004811.616698.Cam6_13.png</td>\n",
       "      <td>92503</td>\n",
       "      <td>{}</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>237.74</td>\n",
       "      <td>174.52</td>\n",
       "      <td>22.90</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T004811.616698.Cam6_13.png</td>\n",
       "      <td>92503</td>\n",
       "      <td>{}</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>200.00</td>\n",
       "      <td>151.29</td>\n",
       "      <td>22.90</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T004811.616698.Cam6_13.png</td>\n",
       "      <td>92503</td>\n",
       "      <td>{}</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>200.32</td>\n",
       "      <td>177.42</td>\n",
       "      <td>22.90</td>\n",
       "      <td>1</td>\n",
       "      <td>20130320T004811.616698.Cam6_13.png</td>\n",
       "      <td>92503</td>\n",
       "      <td>{}</td>\n",
       "      <td>12</td>\n",
       "      <td>11</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "      <td>{}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    #item     c-x     c-y  radius  label                            filename  \\\n",
       "0       0  175.48   96.45   24.51      1  20130320T004811.616698.Cam6_13.png   \n",
       "1       1  164.52   53.87   23.55      1  20130320T004811.616698.Cam6_13.png   \n",
       "2       2  130.00   30.00   23.55      1  20130320T004811.616698.Cam6_13.png   \n",
       "3       3  167.10    7.74   23.55      1  20130320T004811.616698.Cam6_13.png   \n",
       "4       4  196.13   37.42   23.55      1  20130320T004811.616698.Cam6_13.png   \n",
       "5       5  245.48   66.45   23.55      1  20130320T004811.616698.Cam6_13.png   \n",
       "6       6  278.71   48.71   22.90      1  20130320T004811.616698.Cam6_13.png   \n",
       "7       7  285.16   86.77   23.87      1  20130320T004811.616698.Cam6_13.png   \n",
       "8       8  266.45  135.81   22.90      1  20130320T004811.616698.Cam6_13.png   \n",
       "9       9  237.74  174.52   22.90      1  20130320T004811.616698.Cam6_13.png   \n",
       "10     10  200.00  151.29   22.90      1  20130320T004811.616698.Cam6_13.png   \n",
       "11     11  200.32  177.42   22.90      1  20130320T004811.616698.Cam6_13.png   \n",
       "\n",
       "    file_size file_attributes  region_count  region_id  \\\n",
       "0       92503              {}            12          0   \n",
       "1       92503              {}            12          1   \n",
       "2       92503              {}            12          2   \n",
       "3       92503              {}            12          3   \n",
       "4       92503              {}            12          4   \n",
       "5       92503              {}            12          5   \n",
       "6       92503              {}            12          6   \n",
       "7       92503              {}            12          7   \n",
       "8       92503              {}            12          8   \n",
       "9       92503              {}            12          9   \n",
       "10      92503              {}            12         10   \n",
       "11      92503              {}            12         11   \n",
       "\n",
       "                              region_shape_attributes region_attributes  \n",
       "0   {'name': 'polygon', 'all_points_x': [199, 199,...                {}  \n",
       "1   {'name': 'polygon', 'all_points_x': [188, 188,...                {}  \n",
       "2   {'name': 'polygon', 'all_points_x': [153, 153,...                {}  \n",
       "3   {'name': 'polygon', 'all_points_x': [190, 190,...                {}  \n",
       "4   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "5   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "6   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "7   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "8   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "9   {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "10  {'name': 'polygon', 'all_points_x': [201, 201,...                {}  \n",
       "11  {'name': 'polygon', 'all_points_x': [201, 201,...                {}  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kiprono/.local/lib/python3.7/site-packages/ipykernel_launcher.py:25: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
      "of pandas will change to not sort by default.\n",
      "\n",
      "To accept the future behavior, pass 'sort=False'.\n",
      "\n",
      "To retain the current behavior and silence the warning, pass 'sort=True'.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "metadf = pd.DataFrame(columns=['#item', 'c-x', 'c-y', 'radius', 'label', 'filename', 'file_size',\n",
    "       'file_attributes', 'region_count', 'region_id',\n",
    "       'region_shape_attributes', 'region_attributes'])\n",
    "\n",
    "apples = \"../Fruits/dataset/apples/dataset/val_csv\"\n",
    "apples_images = \"../Fruits/dataset/apples/dataset/val\"\n",
    "filesList = os.listdir(apples)\n",
    "for index,files in enumerate(filesList):\n",
    "    file_path = os.path.join(apples,files)\n",
    "    df = pd.read_csv(file_path)\n",
    "    image_name = files.replace(\".csv\",\".png\")\n",
    "    for row in range(len(df)):\n",
    "        df.at[row,\"filename\"] = image_name\n",
    "        img = cv.imread(os.path.join(apples_images,image_name))\n",
    "        df.at[row,\"file_size\"] = Path(os.path.join(apples_images,image_name)).stat().st_size\n",
    "        df.at[row,\"file_attributes\"] = '{}'\n",
    "        df.at[row,\"region_count\"] = len(df)\n",
    "        df.at[row,'region_id'] = row\n",
    "        t = {\"name\":\"polygon\",\"all_points_x\":None,\"all_points_y\":None}\n",
    "        x,y = xy_values(df.at[row,\"c-x\"],df.at[row,\"c-y\"],df.at[row,\"radius\"],img.shape[0],img.shape[1])\n",
    "        t['all_points_x']  = x\n",
    "        t['all_points_y'] = y\n",
    "        df.at[row,'region_shape_attributes'] = object()\n",
    "        df.at[row,'region_shape_attributes'] = t\n",
    "        df.at[row,\"region_attributes\"] = '{}'\n",
    "    metadf = pd.concat([metadf, df], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#item</th>\n",
       "      <th>c-x</th>\n",
       "      <th>c-y</th>\n",
       "      <th>file_attributes</th>\n",
       "      <th>file_size</th>\n",
       "      <th>filename</th>\n",
       "      <th>label</th>\n",
       "      <th>radius</th>\n",
       "      <th>region_attributes</th>\n",
       "      <th>region_count</th>\n",
       "      <th>region_id</th>\n",
       "      <th>region_shape_attributes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>170.62</td>\n",
       "      <td>159.69</td>\n",
       "      <td>{}</td>\n",
       "      <td>98334.0</td>\n",
       "      <td>20130320T004403.421053.Cam6_32.png</td>\n",
       "      <td>1</td>\n",
       "      <td>24.39</td>\n",
       "      <td>{}</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [195, 194,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>195.81</td>\n",
       "      <td>110.00</td>\n",
       "      <td>{}</td>\n",
       "      <td>108751.0</td>\n",
       "      <td>20130320T005044.762746.Cam6_62.png</td>\n",
       "      <td>1</td>\n",
       "      <td>13.87</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>216.13</td>\n",
       "      <td>124.19</td>\n",
       "      <td>{}</td>\n",
       "      <td>108751.0</td>\n",
       "      <td>20130320T005044.762746.Cam6_62.png</td>\n",
       "      <td>1</td>\n",
       "      <td>15.16</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>295.81</td>\n",
       "      <td>89.35</td>\n",
       "      <td>{}</td>\n",
       "      <td>108751.0</td>\n",
       "      <td>20130320T005044.762746.Cam6_62.png</td>\n",
       "      <td>1</td>\n",
       "      <td>11.29</td>\n",
       "      <td>{}</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>87.50</td>\n",
       "      <td>62.22</td>\n",
       "      <td>{}</td>\n",
       "      <td>120851.0</td>\n",
       "      <td>20130320T005748.390478.Cam6_53.png</td>\n",
       "      <td>1</td>\n",
       "      <td>20.09</td>\n",
       "      <td>{}</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [107, 107,...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  #item     c-x     c-y file_attributes  file_size  \\\n",
       "0     0  170.62  159.69              {}    98334.0   \n",
       "1     0  195.81  110.00              {}   108751.0   \n",
       "2     1  216.13  124.19              {}   108751.0   \n",
       "3     2  295.81   89.35              {}   108751.0   \n",
       "4     0   87.50   62.22              {}   120851.0   \n",
       "\n",
       "                             filename label  radius region_attributes  \\\n",
       "0  20130320T004403.421053.Cam6_32.png     1   24.39                {}   \n",
       "1  20130320T005044.762746.Cam6_62.png     1   13.87                {}   \n",
       "2  20130320T005044.762746.Cam6_62.png     1   15.16                {}   \n",
       "3  20130320T005044.762746.Cam6_62.png     1   11.29                {}   \n",
       "4  20130320T005748.390478.Cam6_53.png     1   20.09                {}   \n",
       "\n",
       "   region_count  region_id                            region_shape_attributes  \n",
       "0           1.0        0.0  {'name': 'polygon', 'all_points_x': [195, 194,...  \n",
       "1           3.0        0.0  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "2           3.0        1.0  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "3           3.0        2.0  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4           4.0        0.0  {'name': 'polygon', 'all_points_x': [107, 107,...  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "metadf[\"file_size\"] = metadf[\"file_size\"].astype(\"int64\")\n",
    "metadf[\"region_count\"] = metadf[\"region_count\"].astype(\"int64\")\n",
    "metadf['region_id'] = metadf['region_id'].astype(\"int64\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "metadf2=metadf.drop(['#item', 'c-x','c-y','radius','label'], axis = 1) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>file_attributes</th>\n",
       "      <th>file_size</th>\n",
       "      <th>filename</th>\n",
       "      <th>region_attributes</th>\n",
       "      <th>region_count</th>\n",
       "      <th>region_id</th>\n",
       "      <th>region_shape_attributes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>{}</td>\n",
       "      <td>98334</td>\n",
       "      <td>20130320T004403.421053.Cam6_32.png</td>\n",
       "      <td>{}</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [195, 194,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>{}</td>\n",
       "      <td>108751</td>\n",
       "      <td>20130320T005044.762746.Cam6_62.png</td>\n",
       "      <td>{}</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>{}</td>\n",
       "      <td>108751</td>\n",
       "      <td>20130320T005044.762746.Cam6_62.png</td>\n",
       "      <td>{}</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>{}</td>\n",
       "      <td>108751</td>\n",
       "      <td>20130320T005044.762746.Cam6_62.png</td>\n",
       "      <td>{}</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [201, 201,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>{}</td>\n",
       "      <td>120851</td>\n",
       "      <td>20130320T005748.390478.Cam6_53.png</td>\n",
       "      <td>{}</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>{'name': 'polygon', 'all_points_x': [107, 107,...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  file_attributes  file_size                            filename  \\\n",
       "0              {}      98334  20130320T004403.421053.Cam6_32.png   \n",
       "1              {}     108751  20130320T005044.762746.Cam6_62.png   \n",
       "2              {}     108751  20130320T005044.762746.Cam6_62.png   \n",
       "3              {}     108751  20130320T005044.762746.Cam6_62.png   \n",
       "4              {}     120851  20130320T005748.390478.Cam6_53.png   \n",
       "\n",
       "  region_attributes  region_count  region_id  \\\n",
       "0                {}             1          0   \n",
       "1                {}             3          0   \n",
       "2                {}             3          1   \n",
       "3                {}             3          2   \n",
       "4                {}             4          0   \n",
       "\n",
       "                             region_shape_attributes  \n",
       "0  {'name': 'polygon', 'all_points_x': [195, 194,...  \n",
       "1  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "2  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "3  {'name': 'polygon', 'all_points_x': [201, 201,...  \n",
       "4  {'name': 'polygon', 'all_points_x': [107, 107,...  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadf2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "metadf2 = metadf[['filename', 'file_size',\n",
    "       'file_attributes', 'region_count', 'region_id',\n",
    "       'region_shape_attributes', 'region_attributes']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "metadf2.to_csv(os.path.join(apples_images,'train_final.csv'),index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Note: Make sure to replace ' with \" on the CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "images = \"../Fruits/dataset/apples/dataset/train\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "annotations = json.load(open(\"via_project_apples.json\"))\n",
    "annotations = list(annotations.values())\n",
    "annotations = [a for a in annotations if a['regions']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'filename': '20130320T005452.005817.Cam6_63.png',\n",
       " 'size': '93395',\n",
       " 'regions': [{'shape_attributes': {'name': 'polygon',\n",
       "    'all_points_x': [255,\n",
       "     255,\n",
       "     255,\n",
       "     255,\n",
       "     255,\n",
       "     255,\n",
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       "     234,\n",
       "     236,\n",
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       "     238,\n",
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       "     240,\n",
       "     241,\n",
       "     242,\n",
       "     244,\n",
       "     245,\n",
       "     246,\n",
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       "     248,\n",
       "     249,\n",
       "     249,\n",
       "     250,\n",
       "     251,\n",
       "     252,\n",
       "     252,\n",
       "     253,\n",
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       "     254,\n",
       "     255,\n",
       "     255,\n",
       "     255,\n",
       "     255,\n",
       "     255,\n",
       "     255],\n",
       "    'all_points_y': [135,\n",
       "     136,\n",
       "     137,\n",
       "     138,\n",
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       "     140,\n",
       "     141,\n",
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       "     120,\n",
       "     120,\n",
       "     121,\n",
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       "     123,\n",
       "     124,\n",
       "     125,\n",
       "     126,\n",
       "     127,\n",
       "     128,\n",
       "     129,\n",
       "     130,\n",
       "     131,\n",
       "     132,\n",
       "     133,\n",
       "     135]},\n",
       "   'region_attributes': {}}],\n",
       " 'file_attributes': {}}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "annotations[20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 98 98 195 184 20130320T004403.421053.Cam6_32.png (202, 308, 3)\n",
      "1 98 98 107 82 20130320T005748.390478.Cam6_53.png (202, 308, 3)\n",
      "2 98 98 172 34 20130320T004928.380174.Cam6_52.png (202, 308, 3)\n",
      "3 98 98 278 122 20130320T012845.190374_42.png (202, 308, 3)\n",
      "4 98 98 42 195 20130320T005544.578414.Cam6_22.png (202, 308, 3)\n",
      "5 98 98 88 201 20130320T005553.530973.Cam6_13.png (202, 308, 3)\n",
      "6 98 98 87 177 20130320T005809.533784.Cam6_12.png (202, 308, 3)\n",
      "7 98 98 89 205 20130320T005617.912359.Cam6_63.png (202, 308, 3)\n",
      "8 98 98 132 178 20130320T005108.382236.Cam6_11.png (202, 308, 3)\n",
      "9 98 98 132 100 20130320T005326.289805.Cam6_63.png (202, 308, 3)\n",
      "10 98 98 240 117 20130320T004756.568760.Cam6_41.png (202, 308, 3)\n",
      "11 98 98 215 179 20130320T005044.000731.Cam6_21.png (202, 308, 3)\n",
      "12 98 98 283 111 20130320T013349.958479_61.png (202, 308, 3)\n",
      "13 98 98 117 80 20130320T005132.192216.Cam6_23.png (202, 308, 3)\n",
      "14 98 98 252 45 20130320T005320.384934.Cam6_24.png (202, 308, 3)\n",
      "15 98 98 100 56 20130320T013611.866233_34.png (202, 308, 3)\n",
      "16 98 98 201 117 20130320T004717.329820.Cam6_63.png (202, 308, 3)\n",
      "17 98 98 37 26 20130320T004901.331983.Cam6_61.png (202, 308, 3)\n",
      "18 98 98 59 136 20130320T004918.284713.Cam6_62.png (202, 308, 3)\n",
      "19 98 98 31 77 20130320T004803.616531.Cam6_24.png (202, 308, 3)\n",
      "20 98 98 255 152 20130320T005452.005817.Cam6_63.png (202, 308, 3)\n"
     ]
    }
   ],
   "source": [
    "images = \"../Fruits/dataset/apples/dataset/train\"\n",
    "#image = cv.imread(os.path.join(images,a[\"filename\"]))\n",
    "for j in range(len(annotations)):\n",
    "    a = annotations[j]\n",
    "    x = a[\"regions\"][0][\"shape_attributes\"][\"all_points_x\"]\n",
    "    y = a[\"regions\"][0][\"shape_attributes\"][\"all_points_y\"]\n",
    "    image = cv.imread(os.path.join(images,a[\"filename\"]))\n",
    "    if j==0:\n",
    "        image = cv.imread(os.path.join(images,a[\"filename\"]))\n",
    "        plt.imshow(image)\n",
    "        plt.show()\n",
    "    print(j,len(x),len(y),max(x),max(y),a[\"filename\"],image.shape)\n",
    "    if j ==20:\n",
    "        break\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'20130320T004403.421053.Cam6_32.png'"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = annotations[0]\n",
    "a[\"filename\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7faba8f2af98>"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "image = cv.imread(os.path.join(images,a[\"filename\"]))\n",
    "plt.imshow(image)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = a[\"regions\"][0][\"shape_attributes\"][\"all_points_x\"]\n",
    "y = a[\"regions\"][0][\"shape_attributes\"][\"all_points_y\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "pts = []\n",
    "for i,j in zip(x,y):\n",
    "    pts.append([i,j])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "pts = np.array(pts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "img = cv.polylines(image,[np.int32(pts)],isClosed=True,color=(255,0,0),thickness=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fabb3621828>"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "98"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "98"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
